diff --git a/README.rst b/README.rst
index e6315f9..d86ca9b 100644
--- a/README.rst
+++ b/README.rst
@@ -93,12 +93,6 @@ Limits
 Installation
 ============
 
-.. warning::
-
-    This package is currently in pre-release testing phase for version 0.9.0. The latest release candidate is available
-    on PyPI and can be only installed when explicitly stating the exact version and release candidate, e.g. with
-    ``pip install tmtoolkit[recommended]==0.9.0rc3``.
-
 
 The package *tmtoolkit* is available on `PyPI <https://pypi.org/project/tmtoolkit/>`_ and can be installed via
 Python package manager *pip*. It is highly recommended to install tmtoolkit and its dependencies in a
diff --git a/doc/source/data/news_articles_100.xlsx b/doc/source/data/news_articles_100.xlsx
index 50ae51d..c498e20 100644
Binary files a/doc/source/data/news_articles_100.xlsx and b/doc/source/data/news_articles_100.xlsx differ
diff --git a/doc/source/install.rst b/doc/source/install.rst
index 37ab46e..37d879e 100644
--- a/doc/source/install.rst
+++ b/doc/source/install.rst
@@ -3,12 +3,6 @@
 Installation
 ============
 
-.. warning::
-
-    This package is currently in pre-release testing phase for version 0.9.0. The latest release candidate is available
-    on PyPI and can be only installed when explicitly stating the exact version and release candidate, e.g. with
-    ``pip install tmtoolkit[recommended]==0.9.0rc3``.
-
 The package *tmtoolkit* is available on `PyPI <https://pypi.org/project/tmtoolkit/>`_ and can be installed via
 Python package manager *pip*. It is highly recommended to install tmtoolkit and its dependencies in a
 `Python Virtual Environment ("venv") <https://docs.python.org/3/tutorial/venv.html>`_ and upgrade to the latest
diff --git a/doc/source/intro.rst b/doc/source/intro.rst
index 4a7eb09..5a4321e 100644
--- a/doc/source/intro.rst
+++ b/doc/source/intro.rst
@@ -1,6 +1,8 @@
 tmtookit: Text mining and topic modeling toolkit
 ================================================
 
+|pypi| |pypi_downloads| |rtd| |travis| |coverage|
+
 *tmtoolkit* is a set of tools for text mining and topic modeling with Python developed especially for the use in the
 social sciences. It aims for easy installation, extensive documentation and a clear programming interface while
 offering good performance on large datasets by the means of vectorized operations (via NumPy) and parallel computation
@@ -112,3 +114,24 @@ to follow along using these notebooks, you can
 
 There are also a few other examples as plain Python scripts available in the
 `examples folder <https://github.com/WZBSocialScienceCenter/tmtoolkit/tree/master/examples>`_ of the GitHub repository.
+
+
+.. |pypi| image:: https://badge.fury.io/py/tmtoolkit.svg
+    :target: https://badge.fury.io/py/tmtoolkit
+    :alt: PyPI Version
+
+.. |pypi_downloads| image:: https://img.shields.io/pypi/dm/tmtoolkit
+    :target: https://pypi.org/project/tmtoolkit/
+    :alt: Downloads from PyPI
+
+.. |travis| image:: https://travis-ci.org/WZBSocialScienceCenter/tmtoolkit.svg?branch=master
+    :target: https://travis-ci.org/WZBSocialScienceCenter/tmtoolkit
+    :alt: Travis CI Build Status
+
+.. |coverage| image:: https://raw.githubusercontent.com/WZBSocialScienceCenter/tmtoolkit/master/coverage.svg?sanitize=true
+    :target: https://github.com/WZBSocialScienceCenter/tmtoolkit/tree/master/tests
+    :alt: Coverage status
+
+.. |rtd| image:: https://readthedocs.org/projects/tmtoolkit/badge/?version=latest
+    :target: https://tmtoolkit.readthedocs.io/en/latest/?badge=latest
+    :alt: Documentation Status
diff --git a/doc/source/preprocessing.ipynb b/doc/source/preprocessing.ipynb
index 1c4b085..1112127 100644
--- a/doc/source/preprocessing.ipynb
+++ b/doc/source/preprocessing.ipynb
@@ -3154,7 +3154,7 @@
     {
      "data": {
       "text/plain": [
-       "(140408456194312, 140408456194312)"
+       "(139932303304072, 139932303304072)"
       ]
      },
      "execution_count": 79,
@@ -3258,7 +3258,7 @@
     {
      "data": {
       "text/plain": [
-       "(140408456194480, 140408456194312)"
+       "(139931125296264, 139932303304072)"
       ]
      },
      "execution_count": 84,
@@ -3609,31 +3609,31 @@
        "<div class='datatable'>\n",
        "  <table class='frame'>\n",
        "  <thead>\n",
-       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_length</th><th>meta_upper</th></tr>\n",
-       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='boolean' title='bool8'>&#x25AA;</td></tr>\n",
+       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_upper</th><th>meta_length</th></tr>\n",
+       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='boolean' title='bool8'>&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td></tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
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-       "    <tr><td class='row_index'>13</td><td>NewsArticles-1</td><td>13</td><td>Michigan</td><td>8</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>14</td><td>NewsArticles-1</td><td>14</td><td>billionaire</td><td>11</td><td>0</td></tr>\n",
+       "    <tr><td class='row_index'>0</td><td>NewsArticles-1</td><td>0</td><td>Betsy</td><td>0</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>1</td><td>NewsArticles-1</td><td>1</td><td>DeVos</td><td>0</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>2</td><td>NewsArticles-1</td><td>2</td><td>Confirmed</td><td>0</td><td>9</td></tr>\n",
+       "    <tr><td class='row_index'>3</td><td>NewsArticles-1</td><td>3</td><td>as</td><td>0</td><td>2</td></tr>\n",
+       "    <tr><td class='row_index'>4</td><td>NewsArticles-1</td><td>4</td><td>Education</td><td>0</td><td>9</td></tr>\n",
+       "    <tr><td class='row_index'>5</td><td>NewsArticles-1</td><td>5</td><td>Secretary</td><td>0</td><td>9</td></tr>\n",
+       "    <tr><td class='row_index'>6</td><td>NewsArticles-1</td><td>6</td><td>,</td><td>0</td><td>1</td></tr>\n",
+       "    <tr><td class='row_index'>7</td><td>NewsArticles-1</td><td>7</td><td>With</td><td>0</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>8</td><td>NewsArticles-1</td><td>8</td><td>Pence</td><td>0</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>9</td><td>NewsArticles-1</td><td>9</td><td>Casting</td><td>0</td><td>7</td></tr>\n",
+       "    <tr><td class='row_index'>10</td><td>NewsArticles-1</td><td>10</td><td>Historic</td><td>0</td><td>8</td></tr>\n",
+       "    <tr><td class='row_index'>11</td><td>NewsArticles-1</td><td>11</td><td>Tie-Breaking</td><td>0</td><td>12</td></tr>\n",
+       "    <tr><td class='row_index'>12</td><td>NewsArticles-1</td><td>12</td><td>Vote</td><td>0</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>13</td><td>NewsArticles-1</td><td>13</td><td>Michigan</td><td>0</td><td>8</td></tr>\n",
+       "    <tr><td class='row_index'>14</td><td>NewsArticles-1</td><td>14</td><td>billionaire</td><td>0</td><td>11</td></tr>\n",
        "    <tr><td class='row_index'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td></tr>\n",
-       "    <tr><td class='row_index'>2,452,721</td><td>NewsArticles-999</td><td>589</td><td>article</td><td>7</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>2,452,722</td><td>NewsArticles-999</td><td>590</td><td>was</td><td>3</td><td>0</td></tr>\n",
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-       "    <tr><td class='row_index'>2,452,724</td><td>NewsArticles-999</td><td>592</td><td>funny</td><td>5</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>2,452,725</td><td>NewsArticles-999</td><td>593</td><td>?</td><td>1</td><td>0</td></tr>\n",
+       "    <tr><td class='row_index'>2,452,721</td><td>NewsArticles-999</td><td>589</td><td>article</td><td>0</td><td>7</td></tr>\n",
+       "    <tr><td class='row_index'>2,452,722</td><td>NewsArticles-999</td><td>590</td><td>was</td><td>0</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>2,452,723</td><td>NewsArticles-999</td><td>591</td><td>n't</td><td>0</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>2,452,724</td><td>NewsArticles-999</td><td>592</td><td>funny</td><td>0</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>2,452,725</td><td>NewsArticles-999</td><td>593</td><td>?</td><td>0</td><td>1</td></tr>\n",
        "  </tbody>\n",
        "  </table>\n",
        "  <div class='footer'>\n",
@@ -3676,31 +3676,31 @@
        "<div class='datatable'>\n",
        "  <table class='frame'>\n",
        "  <thead>\n",
-       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_length</th><th>meta_upper</th></tr>\n",
-       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='boolean' title='bool8'>&#x25AA;</td></tr>\n",
+       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_upper</th><th>meta_length</th></tr>\n",
+       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='boolean' title='bool8'>&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td></tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
-       "    <tr><td class='row_index'>0</td><td>NewsArticles-1</td><td>466</td><td>ABC</td><td>3</td><td>1</td></tr>\n",
+       "    <tr><td class='row_index'>0</td><td>NewsArticles-1</td><td>466</td><td>ABC</td><td>1</td><td>3</td></tr>\n",
        "    <tr><td class='row_index'>1</td><td>NewsArticles-10</td><td>10</td><td>A</td><td>1</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>2</td><td>NewsArticles-10</td><td>109</td><td>U.S</td><td>3</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>3</td><td>NewsArticles-10</td><td>225</td><td>ABC</td><td>3</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>4</td><td>NewsArticles-10</td><td>227</td><td>WEAR</td><td>4</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>5</td><td>NewsArticles-10</td><td>290</td><td>AP</td><td>2</td><td>1</td></tr>\n",
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-       "    <tr><td class='row_index'>8</td><td>NewsArticles-100</td><td>108</td><td>UK</td><td>2</td><td>1</td></tr>\n",
+       "    <tr><td class='row_index'>2</td><td>NewsArticles-10</td><td>109</td><td>U.S</td><td>1</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>3</td><td>NewsArticles-10</td><td>225</td><td>ABC</td><td>1</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>4</td><td>NewsArticles-10</td><td>227</td><td>WEAR</td><td>1</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>5</td><td>NewsArticles-10</td><td>290</td><td>AP</td><td>1</td><td>2</td></tr>\n",
+       "    <tr><td class='row_index'>6</td><td>NewsArticles-10</td><td>373</td><td>9613BJ</td><td>1</td><td>6</td></tr>\n",
+       "    <tr><td class='row_index'>7</td><td>NewsArticles-100</td><td>97</td><td>UK</td><td>1</td><td>2</td></tr>\n",
+       "    <tr><td class='row_index'>8</td><td>NewsArticles-100</td><td>108</td><td>UK</td><td>1</td><td>2</td></tr>\n",
        "    <tr><td class='row_index'>9</td><td>NewsArticles-100</td><td>326</td><td>C</td><td>1</td><td>1</td></tr>\n",
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-       "    <tr><td class='row_index'>11</td><td>NewsArticles-100</td><td>581</td><td>UK</td><td>2</td><td>1</td></tr>\n",
+       "    <tr><td class='row_index'>11</td><td>NewsArticles-100</td><td>581</td><td>UK</td><td>1</td><td>2</td></tr>\n",
        "    <tr><td class='row_index'>12</td><td>NewsArticles-1000</td><td>11</td><td>A</td><td>1</td><td>1</td></tr>\n",
        "    <tr><td class='row_index'>13</td><td>NewsArticles-1000</td><td>26</td><td>A</td><td>1</td><td>1</td></tr>\n",
        "    <tr><td class='row_index'>14</td><td>NewsArticles-1000</td><td>123</td><td>A</td><td>1</td><td>1</td></tr>\n",
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-       "    <tr><td class='row_index'>36,844</td><td>NewsArticles-999</td><td>490</td><td>U.S</td><td>3</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>36,845</td><td>NewsArticles-999</td><td>495</td><td>LTE</td><td>3</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>36,846</td><td>NewsArticles-999</td><td>515</td><td>4G</td><td>2</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>36,847</td><td>NewsArticles-999</td><td>567</td><td>22-28GB</td><td>7</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>36,848</td><td>NewsArticles-999</td><td>575</td><td>FCC</td><td>3</td><td>1</td></tr>\n",
+       "    <tr><td class='row_index'>36,844</td><td>NewsArticles-999</td><td>490</td><td>U.S</td><td>1</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>36,845</td><td>NewsArticles-999</td><td>495</td><td>LTE</td><td>1</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>36,846</td><td>NewsArticles-999</td><td>515</td><td>4G</td><td>1</td><td>2</td></tr>\n",
+       "    <tr><td class='row_index'>36,847</td><td>NewsArticles-999</td><td>567</td><td>22-28GB</td><td>1</td><td>7</td></tr>\n",
+       "    <tr><td class='row_index'>36,848</td><td>NewsArticles-999</td><td>575</td><td>FCC</td><td>1</td><td>3</td></tr>\n",
        "  </tbody>\n",
        "  </table>\n",
        "  <div class='footer'>\n",
@@ -3741,31 +3741,31 @@
        "<div class='datatable'>\n",
        "  <table class='frame'>\n",
        "  <thead>\n",
-       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_length</th><th>meta_pos</th><th>meta_upper</th></tr>\n",
-       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='boolean' title='bool8'>&#x25AA;</td></tr>\n",
+       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_upper</th><th>meta_pos</th><th>meta_length</th></tr>\n",
+       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='boolean' title='bool8'>&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td></tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
-       "    <tr><td class='row_index'>0</td><td>NewsArticles-1</td><td>0</td><td>Betsy</td><td>5</td><td>NNP</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>1</td><td>NewsArticles-1</td><td>1</td><td>DeVos</td><td>5</td><td>NNP</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>2</td><td>NewsArticles-1</td><td>2</td><td>Confirmed</td><td>9</td><td>NNP</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>3</td><td>NewsArticles-1</td><td>3</td><td>as</td><td>2</td><td>IN</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>4</td><td>NewsArticles-1</td><td>4</td><td>Education</td><td>9</td><td>NNP</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>5</td><td>NewsArticles-1</td><td>5</td><td>Secretary</td><td>9</td><td>NNP</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>6</td><td>NewsArticles-1</td><td>6</td><td>,</td><td>1</td><td>,</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>7</td><td>NewsArticles-1</td><td>7</td><td>With</td><td>4</td><td>IN</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>8</td><td>NewsArticles-1</td><td>8</td><td>Pence</td><td>5</td><td>NNP</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>9</td><td>NewsArticles-1</td><td>9</td><td>Casting</td><td>7</td><td>NNP</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>10</td><td>NewsArticles-1</td><td>10</td><td>Historic</td><td>8</td><td>NNP</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>11</td><td>NewsArticles-1</td><td>11</td><td>Tie-Breaking</td><td>12</td><td>NNP</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>12</td><td>NewsArticles-1</td><td>12</td><td>Vote</td><td>4</td><td>NNP</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>13</td><td>NewsArticles-1</td><td>13</td><td>Michigan</td><td>8</td><td>NNP</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>14</td><td>NewsArticles-1</td><td>14</td><td>billionaire</td><td>11</td><td>POS</td><td>0</td></tr>\n",
+       "    <tr><td class='row_index'>0</td><td>NewsArticles-1</td><td>0</td><td>Betsy</td><td>0</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>1</td><td>NewsArticles-1</td><td>1</td><td>DeVos</td><td>0</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>2</td><td>NewsArticles-1</td><td>2</td><td>Confirmed</td><td>0</td><td>NNP</td><td>9</td></tr>\n",
+       "    <tr><td class='row_index'>3</td><td>NewsArticles-1</td><td>3</td><td>as</td><td>0</td><td>IN</td><td>2</td></tr>\n",
+       "    <tr><td class='row_index'>4</td><td>NewsArticles-1</td><td>4</td><td>Education</td><td>0</td><td>NNP</td><td>9</td></tr>\n",
+       "    <tr><td class='row_index'>5</td><td>NewsArticles-1</td><td>5</td><td>Secretary</td><td>0</td><td>NNP</td><td>9</td></tr>\n",
+       "    <tr><td class='row_index'>6</td><td>NewsArticles-1</td><td>6</td><td>,</td><td>0</td><td>,</td><td>1</td></tr>\n",
+       "    <tr><td class='row_index'>7</td><td>NewsArticles-1</td><td>7</td><td>With</td><td>0</td><td>IN</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>8</td><td>NewsArticles-1</td><td>8</td><td>Pence</td><td>0</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>9</td><td>NewsArticles-1</td><td>9</td><td>Casting</td><td>0</td><td>NNP</td><td>7</td></tr>\n",
+       "    <tr><td class='row_index'>10</td><td>NewsArticles-1</td><td>10</td><td>Historic</td><td>0</td><td>NNP</td><td>8</td></tr>\n",
+       "    <tr><td class='row_index'>11</td><td>NewsArticles-1</td><td>11</td><td>Tie-Breaking</td><td>0</td><td>NNP</td><td>12</td></tr>\n",
+       "    <tr><td class='row_index'>12</td><td>NewsArticles-1</td><td>12</td><td>Vote</td><td>0</td><td>NNP</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>13</td><td>NewsArticles-1</td><td>13</td><td>Michigan</td><td>0</td><td>NNP</td><td>8</td></tr>\n",
+       "    <tr><td class='row_index'>14</td><td>NewsArticles-1</td><td>14</td><td>billionaire</td><td>0</td><td>POS</td><td>11</td></tr>\n",
        "    <tr><td class='row_index'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td></tr>\n",
-       "    <tr><td class='row_index'>2,452,721</td><td>NewsArticles-999</td><td>589</td><td>article</td><td>7</td><td>NN</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>2,452,722</td><td>NewsArticles-999</td><td>590</td><td>was</td><td>3</td><td>VBD</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>2,452,723</td><td>NewsArticles-999</td><td>591</td><td>n't</td><td>3</td><td>RB</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>2,452,724</td><td>NewsArticles-999</td><td>592</td><td>funny</td><td>5</td><td>JJ</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>2,452,725</td><td>NewsArticles-999</td><td>593</td><td>?</td><td>1</td><td>.</td><td>0</td></tr>\n",
+       "    <tr><td class='row_index'>2,452,721</td><td>NewsArticles-999</td><td>589</td><td>article</td><td>0</td><td>NN</td><td>7</td></tr>\n",
+       "    <tr><td class='row_index'>2,452,722</td><td>NewsArticles-999</td><td>590</td><td>was</td><td>0</td><td>VBD</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>2,452,723</td><td>NewsArticles-999</td><td>591</td><td>n't</td><td>0</td><td>RB</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>2,452,724</td><td>NewsArticles-999</td><td>592</td><td>funny</td><td>0</td><td>JJ</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>2,452,725</td><td>NewsArticles-999</td><td>593</td><td>?</td><td>0</td><td>.</td><td>1</td></tr>\n",
        "  </tbody>\n",
        "  </table>\n",
        "  <div class='footer'>\n",
@@ -3878,31 +3878,31 @@
        "<div class='datatable'>\n",
        "  <table class='frame'>\n",
        "  <thead>\n",
-       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_length</th><th>meta_pos</th></tr>\n",
-       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td></tr>\n",
+       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_pos</th><th>meta_length</th></tr>\n",
+       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td></tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
-       "    <tr><td class='row_index'>0</td><td>NewsArticles-1</td><td>0</td><td>Betsy</td><td>5</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>1</td><td>NewsArticles-1</td><td>1</td><td>DeVos</td><td>5</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>2</td><td>NewsArticles-1</td><td>2</td><td>Confirmed</td><td>9</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>3</td><td>NewsArticles-1</td><td>3</td><td>as</td><td>2</td><td>IN</td></tr>\n",
-       "    <tr><td class='row_index'>4</td><td>NewsArticles-1</td><td>4</td><td>Education</td><td>9</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>5</td><td>NewsArticles-1</td><td>5</td><td>Secretary</td><td>9</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>6</td><td>NewsArticles-1</td><td>6</td><td>,</td><td>1</td><td>,</td></tr>\n",
-       "    <tr><td class='row_index'>7</td><td>NewsArticles-1</td><td>7</td><td>With</td><td>4</td><td>IN</td></tr>\n",
-       "    <tr><td class='row_index'>8</td><td>NewsArticles-1</td><td>8</td><td>Pence</td><td>5</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>9</td><td>NewsArticles-1</td><td>9</td><td>Casting</td><td>7</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>10</td><td>NewsArticles-1</td><td>10</td><td>Historic</td><td>8</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>11</td><td>NewsArticles-1</td><td>11</td><td>Tie-Breaking</td><td>12</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>12</td><td>NewsArticles-1</td><td>12</td><td>Vote</td><td>4</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>13</td><td>NewsArticles-1</td><td>13</td><td>Michigan</td><td>8</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>14</td><td>NewsArticles-1</td><td>14</td><td>billionaire</td><td>11</td><td>POS</td></tr>\n",
+       "    <tr><td class='row_index'>0</td><td>NewsArticles-1</td><td>0</td><td>Betsy</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>1</td><td>NewsArticles-1</td><td>1</td><td>DeVos</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>2</td><td>NewsArticles-1</td><td>2</td><td>Confirmed</td><td>NNP</td><td>9</td></tr>\n",
+       "    <tr><td class='row_index'>3</td><td>NewsArticles-1</td><td>3</td><td>as</td><td>IN</td><td>2</td></tr>\n",
+       "    <tr><td class='row_index'>4</td><td>NewsArticles-1</td><td>4</td><td>Education</td><td>NNP</td><td>9</td></tr>\n",
+       "    <tr><td class='row_index'>5</td><td>NewsArticles-1</td><td>5</td><td>Secretary</td><td>NNP</td><td>9</td></tr>\n",
+       "    <tr><td class='row_index'>6</td><td>NewsArticles-1</td><td>6</td><td>,</td><td>,</td><td>1</td></tr>\n",
+       "    <tr><td class='row_index'>7</td><td>NewsArticles-1</td><td>7</td><td>With</td><td>IN</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>8</td><td>NewsArticles-1</td><td>8</td><td>Pence</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>9</td><td>NewsArticles-1</td><td>9</td><td>Casting</td><td>NNP</td><td>7</td></tr>\n",
+       "    <tr><td class='row_index'>10</td><td>NewsArticles-1</td><td>10</td><td>Historic</td><td>NNP</td><td>8</td></tr>\n",
+       "    <tr><td class='row_index'>11</td><td>NewsArticles-1</td><td>11</td><td>Tie-Breaking</td><td>NNP</td><td>12</td></tr>\n",
+       "    <tr><td class='row_index'>12</td><td>NewsArticles-1</td><td>12</td><td>Vote</td><td>NNP</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>13</td><td>NewsArticles-1</td><td>13</td><td>Michigan</td><td>NNP</td><td>8</td></tr>\n",
+       "    <tr><td class='row_index'>14</td><td>NewsArticles-1</td><td>14</td><td>billionaire</td><td>POS</td><td>11</td></tr>\n",
        "    <tr><td class='row_index'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td></tr>\n",
-       "    <tr><td class='row_index'>2,452,721</td><td>NewsArticles-999</td><td>589</td><td>article</td><td>7</td><td>NN</td></tr>\n",
-       "    <tr><td class='row_index'>2,452,722</td><td>NewsArticles-999</td><td>590</td><td>be</td><td>3</td><td>VBD</td></tr>\n",
-       "    <tr><td class='row_index'>2,452,723</td><td>NewsArticles-999</td><td>591</td><td>n't</td><td>3</td><td>RB</td></tr>\n",
-       "    <tr><td class='row_index'>2,452,724</td><td>NewsArticles-999</td><td>592</td><td>funny</td><td>5</td><td>JJ</td></tr>\n",
-       "    <tr><td class='row_index'>2,452,725</td><td>NewsArticles-999</td><td>593</td><td>?</td><td>1</td><td>.</td></tr>\n",
+       "    <tr><td class='row_index'>2,452,721</td><td>NewsArticles-999</td><td>589</td><td>article</td><td>NN</td><td>7</td></tr>\n",
+       "    <tr><td class='row_index'>2,452,722</td><td>NewsArticles-999</td><td>590</td><td>be</td><td>VBD</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>2,452,723</td><td>NewsArticles-999</td><td>591</td><td>n't</td><td>RB</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>2,452,724</td><td>NewsArticles-999</td><td>592</td><td>funny</td><td>JJ</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>2,452,725</td><td>NewsArticles-999</td><td>593</td><td>?</td><td>.</td><td>1</td></tr>\n",
        "  </tbody>\n",
        "  </table>\n",
        "  <div class='footer'>\n",
@@ -3942,31 +3942,31 @@
        "<div class='datatable'>\n",
        "  <table class='frame'>\n",
        "  <thead>\n",
-       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_length</th><th>meta_pos</th></tr>\n",
-       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td></tr>\n",
+       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_pos</th><th>meta_length</th></tr>\n",
+       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td></tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
-       "    <tr><td class='row_index'>0</td><td>NewsArticles-1</td><td>0</td><td>betsy</td><td>5</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>1</td><td>NewsArticles-1</td><td>1</td><td>devos</td><td>5</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>2</td><td>NewsArticles-1</td><td>2</td><td>confirmed</td><td>9</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>3</td><td>NewsArticles-1</td><td>3</td><td>education</td><td>9</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>4</td><td>NewsArticles-1</td><td>4</td><td>secretary</td><td>9</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>5</td><td>NewsArticles-1</td><td>5</td><td>pence</td><td>5</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>6</td><td>NewsArticles-1</td><td>6</td><td>casting</td><td>7</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>7</td><td>NewsArticles-1</td><td>7</td><td>historic</td><td>8</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>8</td><td>NewsArticles-1</td><td>8</td><td>tie-breaking</td><td>12</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>9</td><td>NewsArticles-1</td><td>9</td><td>vote</td><td>4</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>10</td><td>NewsArticles-1</td><td>10</td><td>michigan</td><td>8</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>11</td><td>NewsArticles-1</td><td>11</td><td>billionaire</td><td>11</td><td>POS</td></tr>\n",
-       "    <tr><td class='row_index'>12</td><td>NewsArticles-1</td><td>12</td><td>education</td><td>9</td><td>NN</td></tr>\n",
-       "    <tr><td class='row_index'>13</td><td>NewsArticles-1</td><td>13</td><td>activist</td><td>8</td><td>NN</td></tr>\n",
-       "    <tr><td class='row_index'>14</td><td>NewsArticles-1</td><td>14</td><td>betsy</td><td>5</td><td>NNP</td></tr>\n",
+       "    <tr><td class='row_index'>0</td><td>NewsArticles-1</td><td>0</td><td>betsy</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>1</td><td>NewsArticles-1</td><td>1</td><td>devos</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>2</td><td>NewsArticles-1</td><td>2</td><td>confirmed</td><td>NNP</td><td>9</td></tr>\n",
+       "    <tr><td class='row_index'>3</td><td>NewsArticles-1</td><td>3</td><td>education</td><td>NNP</td><td>9</td></tr>\n",
+       "    <tr><td class='row_index'>4</td><td>NewsArticles-1</td><td>4</td><td>secretary</td><td>NNP</td><td>9</td></tr>\n",
+       "    <tr><td class='row_index'>5</td><td>NewsArticles-1</td><td>5</td><td>pence</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>6</td><td>NewsArticles-1</td><td>6</td><td>casting</td><td>NNP</td><td>7</td></tr>\n",
+       "    <tr><td class='row_index'>7</td><td>NewsArticles-1</td><td>7</td><td>historic</td><td>NNP</td><td>8</td></tr>\n",
+       "    <tr><td class='row_index'>8</td><td>NewsArticles-1</td><td>8</td><td>tie-breaking</td><td>NNP</td><td>12</td></tr>\n",
+       "    <tr><td class='row_index'>9</td><td>NewsArticles-1</td><td>9</td><td>vote</td><td>NNP</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>10</td><td>NewsArticles-1</td><td>10</td><td>michigan</td><td>NNP</td><td>8</td></tr>\n",
+       "    <tr><td class='row_index'>11</td><td>NewsArticles-1</td><td>11</td><td>billionaire</td><td>POS</td><td>11</td></tr>\n",
+       "    <tr><td class='row_index'>12</td><td>NewsArticles-1</td><td>12</td><td>education</td><td>NN</td><td>9</td></tr>\n",
+       "    <tr><td class='row_index'>13</td><td>NewsArticles-1</td><td>13</td><td>activist</td><td>NN</td><td>8</td></tr>\n",
+       "    <tr><td class='row_index'>14</td><td>NewsArticles-1</td><td>14</td><td>betsy</td><td>NNP</td><td>5</td></tr>\n",
        "    <tr><td class='row_index'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td></tr>\n",
-       "    <tr><td class='row_index'>1,313,679</td><td>NewsArticles-999</td><td>275</td><td>away</td><td>4</td><td>RB</td></tr>\n",
-       "    <tr><td class='row_index'>1,313,680</td><td>NewsArticles-999</td><td>276</td><td>think</td><td>7</td><td>VBD</td></tr>\n",
-       "    <tr><td class='row_index'>1,313,681</td><td>NewsArticles-999</td><td>277</td><td>article</td><td>7</td><td>NN</td></tr>\n",
-       "    <tr><td class='row_index'>1,313,682</td><td>NewsArticles-999</td><td>278</td><td>n't</td><td>3</td><td>RB</td></tr>\n",
-       "    <tr><td class='row_index'>1,313,683</td><td>NewsArticles-999</td><td>279</td><td>funny</td><td>5</td><td>JJ</td></tr>\n",
+       "    <tr><td class='row_index'>1,313,679</td><td>NewsArticles-999</td><td>275</td><td>away</td><td>RB</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>1,313,680</td><td>NewsArticles-999</td><td>276</td><td>think</td><td>VBD</td><td>7</td></tr>\n",
+       "    <tr><td class='row_index'>1,313,681</td><td>NewsArticles-999</td><td>277</td><td>article</td><td>NN</td><td>7</td></tr>\n",
+       "    <tr><td class='row_index'>1,313,682</td><td>NewsArticles-999</td><td>278</td><td>n't</td><td>RB</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>1,313,683</td><td>NewsArticles-999</td><td>279</td><td>funny</td><td>JJ</td><td>5</td></tr>\n",
        "  </tbody>\n",
        "  </table>\n",
        "  <div class='footer'>\n",
@@ -3999,31 +3999,31 @@
        "<div class='datatable'>\n",
        "  <table class='frame'>\n",
        "  <thead>\n",
-       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_length</th><th>meta_pos</th></tr>\n",
-       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td></tr>\n",
+       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_pos</th><th>meta_length</th></tr>\n",
+       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td></tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
-       "    <tr><td class='row_index'>0</td><td>NewsArticles-1</td><td>0</td><td>betsy</td><td>5</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>1</td><td>NewsArticles-1</td><td>1</td><td>devos</td><td>5</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>2</td><td>NewsArticles-1</td><td>2</td><td>education</td><td>9</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>3</td><td>NewsArticles-1</td><td>3</td><td>secretary</td><td>9</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>4</td><td>NewsArticles-1</td><td>4</td><td>pence</td><td>5</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>5</td><td>NewsArticles-1</td><td>5</td><td>historic</td><td>8</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>6</td><td>NewsArticles-1</td><td>6</td><td>vote</td><td>4</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>7</td><td>NewsArticles-1</td><td>7</td><td>michigan</td><td>8</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>8</td><td>NewsArticles-1</td><td>8</td><td>billionaire</td><td>11</td><td>POS</td></tr>\n",
-       "    <tr><td class='row_index'>9</td><td>NewsArticles-1</td><td>9</td><td>education</td><td>9</td><td>NN</td></tr>\n",
-       "    <tr><td class='row_index'>10</td><td>NewsArticles-1</td><td>10</td><td>activist</td><td>8</td><td>NN</td></tr>\n",
-       "    <tr><td class='row_index'>11</td><td>NewsArticles-1</td><td>11</td><td>betsy</td><td>5</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>12</td><td>NewsArticles-1</td><td>12</td><td>devos</td><td>5</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>13</td><td>NewsArticles-1</td><td>13</td><td>confirm</td><td>9</td><td>VBN</td></tr>\n",
-       "    <tr><td class='row_index'>14</td><td>NewsArticles-1</td><td>14</td><td>today</td><td>5</td><td>NN</td></tr>\n",
+       "    <tr><td class='row_index'>0</td><td>NewsArticles-1</td><td>0</td><td>betsy</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>1</td><td>NewsArticles-1</td><td>1</td><td>devos</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>2</td><td>NewsArticles-1</td><td>2</td><td>education</td><td>NNP</td><td>9</td></tr>\n",
+       "    <tr><td class='row_index'>3</td><td>NewsArticles-1</td><td>3</td><td>secretary</td><td>NNP</td><td>9</td></tr>\n",
+       "    <tr><td class='row_index'>4</td><td>NewsArticles-1</td><td>4</td><td>pence</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>5</td><td>NewsArticles-1</td><td>5</td><td>historic</td><td>NNP</td><td>8</td></tr>\n",
+       "    <tr><td class='row_index'>6</td><td>NewsArticles-1</td><td>6</td><td>vote</td><td>NNP</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>7</td><td>NewsArticles-1</td><td>7</td><td>michigan</td><td>NNP</td><td>8</td></tr>\n",
+       "    <tr><td class='row_index'>8</td><td>NewsArticles-1</td><td>8</td><td>billionaire</td><td>POS</td><td>11</td></tr>\n",
+       "    <tr><td class='row_index'>9</td><td>NewsArticles-1</td><td>9</td><td>education</td><td>NN</td><td>9</td></tr>\n",
+       "    <tr><td class='row_index'>10</td><td>NewsArticles-1</td><td>10</td><td>activist</td><td>NN</td><td>8</td></tr>\n",
+       "    <tr><td class='row_index'>11</td><td>NewsArticles-1</td><td>11</td><td>betsy</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>12</td><td>NewsArticles-1</td><td>12</td><td>devos</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>13</td><td>NewsArticles-1</td><td>13</td><td>confirm</td><td>VBN</td><td>9</td></tr>\n",
+       "    <tr><td class='row_index'>14</td><td>NewsArticles-1</td><td>14</td><td>today</td><td>NN</td><td>5</td></tr>\n",
        "    <tr><td class='row_index'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td></tr>\n",
-       "    <tr><td class='row_index'>1,183,399</td><td>NewsArticles-999</td><td>219</td><td>away</td><td>4</td><td>RB</td></tr>\n",
-       "    <tr><td class='row_index'>1,183,400</td><td>NewsArticles-999</td><td>220</td><td>think</td><td>7</td><td>VBD</td></tr>\n",
-       "    <tr><td class='row_index'>1,183,401</td><td>NewsArticles-999</td><td>221</td><td>article</td><td>7</td><td>NN</td></tr>\n",
-       "    <tr><td class='row_index'>1,183,402</td><td>NewsArticles-999</td><td>222</td><td>n't</td><td>3</td><td>RB</td></tr>\n",
-       "    <tr><td class='row_index'>1,183,403</td><td>NewsArticles-999</td><td>223</td><td>funny</td><td>5</td><td>JJ</td></tr>\n",
+       "    <tr><td class='row_index'>1,183,399</td><td>NewsArticles-999</td><td>219</td><td>away</td><td>RB</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>1,183,400</td><td>NewsArticles-999</td><td>220</td><td>think</td><td>VBD</td><td>7</td></tr>\n",
+       "    <tr><td class='row_index'>1,183,401</td><td>NewsArticles-999</td><td>221</td><td>article</td><td>NN</td><td>7</td></tr>\n",
+       "    <tr><td class='row_index'>1,183,402</td><td>NewsArticles-999</td><td>222</td><td>n't</td><td>RB</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>1,183,403</td><td>NewsArticles-999</td><td>223</td><td>funny</td><td>JJ</td><td>5</td></tr>\n",
        "  </tbody>\n",
        "  </table>\n",
        "  <div class='footer'>\n",
@@ -4092,31 +4092,31 @@
        "<div class='datatable'>\n",
        "  <table class='frame'>\n",
        "  <thead>\n",
-       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_length</th><th>meta_pos</th></tr>\n",
-       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td></tr>\n",
+       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_pos</th><th>meta_length</th></tr>\n",
+       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td></tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
-       "    <tr><td class='row_index'>0</td><td>NewsArticles-1</td><td>0</td><td>use</td><td>3</td><td>VB</td></tr>\n",
-       "    <tr><td class='row_index'>1</td><td>NewsArticles-1</td><td>1</td><td>tie</td><td>3</td><td>NN</td></tr>\n",
-       "    <tr><td class='row_index'>2</td><td>NewsArticles-1</td><td>2</td><td>day</td><td>3</td><td>NN</td></tr>\n",
-       "    <tr><td class='row_index'>3</td><td>NewsArticles-1</td><td>3</td><td>one</td><td>3</td><td>CD</td></tr>\n",
-       "    <tr><td class='row_index'>4</td><td>NewsArticles-1</td><td>4</td><td>sen</td><td>3</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>5</td><td>NewsArticles-1</td><td>5</td><td>law</td><td>3</td><td>NN</td></tr>\n",
-       "    <tr><td class='row_index'>6</td><td>NewsArticles-1</td><td>6</td><td>van</td><td>3</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>7</td><td>NewsArticles-1</td><td>7</td><td>two</td><td>3</td><td>CD</td></tr>\n",
-       "    <tr><td class='row_index'>8</td><td>NewsArticles-1</td><td>8</td><td>abc</td><td>3</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>9</td><td>NewsArticles-10</td><td>0</td><td>run</td><td>3</td><td>NN</td></tr>\n",
-       "    <tr><td class='row_index'>10</td><td>NewsArticles-10</td><td>1</td><td>may</td><td>3</td><td>MD</td></tr>\n",
-       "    <tr><td class='row_index'>11</td><td>NewsArticles-10</td><td>2</td><td>u.s</td><td>3</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>12</td><td>NewsArticles-10</td><td>3</td><td>abc</td><td>3</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>13</td><td>NewsArticles-10</td><td>4</td><td>say</td><td>3</td><td>VBP</td></tr>\n",
-       "    <tr><td class='row_index'>14</td><td>NewsArticles-10</td><td>5</td><td>duo</td><td>3</td><td>NN</td></tr>\n",
+       "    <tr><td class='row_index'>0</td><td>NewsArticles-1</td><td>0</td><td>use</td><td>VB</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>1</td><td>NewsArticles-1</td><td>1</td><td>tie</td><td>NN</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>2</td><td>NewsArticles-1</td><td>2</td><td>day</td><td>NN</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>3</td><td>NewsArticles-1</td><td>3</td><td>one</td><td>CD</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>4</td><td>NewsArticles-1</td><td>4</td><td>sen</td><td>NNP</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>5</td><td>NewsArticles-1</td><td>5</td><td>law</td><td>NN</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>6</td><td>NewsArticles-1</td><td>6</td><td>van</td><td>NNP</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>7</td><td>NewsArticles-1</td><td>7</td><td>two</td><td>CD</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>8</td><td>NewsArticles-1</td><td>8</td><td>abc</td><td>NNP</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>9</td><td>NewsArticles-10</td><td>0</td><td>run</td><td>NN</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>10</td><td>NewsArticles-10</td><td>1</td><td>may</td><td>MD</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>11</td><td>NewsArticles-10</td><td>2</td><td>u.s</td><td>NNP</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>12</td><td>NewsArticles-10</td><td>3</td><td>abc</td><td>NNP</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>13</td><td>NewsArticles-10</td><td>4</td><td>say</td><td>VBP</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>14</td><td>NewsArticles-10</td><td>5</td><td>duo</td><td>NN</td><td>3</td></tr>\n",
        "    <tr><td class='row_index'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td></tr>\n",
-       "    <tr><td class='row_index'>70,182</td><td>NewsArticles-999</td><td>19</td><td>n't</td><td>3</td><td>RB</td></tr>\n",
-       "    <tr><td class='row_index'>70,183</td><td>NewsArticles-999</td><td>20</td><td>new</td><td>3</td><td>JJ</td></tr>\n",
-       "    <tr><td class='row_index'>70,184</td><td>NewsArticles-999</td><td>21</td><td>n't</td><td>3</td><td>RB</td></tr>\n",
-       "    <tr><td class='row_index'>70,185</td><td>NewsArticles-999</td><td>22</td><td>new</td><td>3</td><td>JJ</td></tr>\n",
-       "    <tr><td class='row_index'>70,186</td><td>NewsArticles-999</td><td>23</td><td>n't</td><td>3</td><td>RB</td></tr>\n",
+       "    <tr><td class='row_index'>70,182</td><td>NewsArticles-999</td><td>19</td><td>n't</td><td>RB</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>70,183</td><td>NewsArticles-999</td><td>20</td><td>new</td><td>JJ</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>70,184</td><td>NewsArticles-999</td><td>21</td><td>n't</td><td>RB</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>70,185</td><td>NewsArticles-999</td><td>22</td><td>new</td><td>JJ</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>70,186</td><td>NewsArticles-999</td><td>23</td><td>n't</td><td>RB</td><td>3</td></tr>\n",
        "  </tbody>\n",
        "  </table>\n",
        "  <div class='footer'>\n",
@@ -4156,31 +4156,31 @@
        "<div class='datatable'>\n",
        "  <table class='frame'>\n",
        "  <thead>\n",
-       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_length</th><th>meta_pos</th></tr>\n",
-       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td></tr>\n",
+       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_pos</th><th>meta_length</th></tr>\n",
+       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td></tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
-       "    <tr><td class='row_index'>0</td><td>NewsArticles-1728</td><td>0</td><td>Trump</td><td>5</td><td>NN</td></tr>\n",
-       "    <tr><td class='row_index'>1</td><td>NewsArticles-1728</td><td>1</td><td>:</td><td>1</td><td>:</td></tr>\n",
-       "    <tr><td class='row_index'>2</td><td>NewsArticles-1728</td><td>2</td><td>Agency</td><td>6</td><td>NN</td></tr>\n",
-       "    <tr><td class='row_index'>3</td><td>NewsArticles-1728</td><td>3</td><td>to</td><td>2</td><td>TO</td></tr>\n",
-       "    <tr><td class='row_index'>4</td><td>NewsArticles-1728</td><td>4</td><td>support</td><td>7</td><td>VB</td></tr>\n",
-       "    <tr><td class='row_index'>5</td><td>NewsArticles-1728</td><td>5</td><td>'victims</td><td>8</td><td>NNS</td></tr>\n",
-       "    <tr><td class='row_index'>6</td><td>NewsArticles-1728</td><td>6</td><td>of</td><td>2</td><td>IN</td></tr>\n",
-       "    <tr><td class='row_index'>7</td><td>NewsArticles-1728</td><td>7</td><td>immigrant</td><td>9</td><td>JJ</td></tr>\n",
-       "    <tr><td class='row_index'>8</td><td>NewsArticles-1728</td><td>8</td><td>crimes'</td><td>7</td><td>NN</td></tr>\n",
-       "    <tr><td class='row_index'>9</td><td>NewsArticles-1728</td><td>9</td><td>In</td><td>2</td><td>IN</td></tr>\n",
-       "    <tr><td class='row_index'>10</td><td>NewsArticles-1728</td><td>10</td><td>first</td><td>5</td><td>JJ</td></tr>\n",
-       "    <tr><td class='row_index'>11</td><td>NewsArticles-1728</td><td>11</td><td>speech</td><td>6</td><td>NN</td></tr>\n",
-       "    <tr><td class='row_index'>12</td><td>NewsArticles-1728</td><td>12</td><td>to</td><td>2</td><td>TO</td></tr>\n",
-       "    <tr><td class='row_index'>13</td><td>NewsArticles-1728</td><td>13</td><td>Congress</td><td>8</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>14</td><td>NewsArticles-1728</td><td>14</td><td>,</td><td>1</td><td>,</td></tr>\n",
+       "    <tr><td class='row_index'>0</td><td>NewsArticles-1728</td><td>0</td><td>Trump</td><td>NN</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>1</td><td>NewsArticles-1728</td><td>1</td><td>:</td><td>:</td><td>1</td></tr>\n",
+       "    <tr><td class='row_index'>2</td><td>NewsArticles-1728</td><td>2</td><td>Agency</td><td>NN</td><td>6</td></tr>\n",
+       "    <tr><td class='row_index'>3</td><td>NewsArticles-1728</td><td>3</td><td>to</td><td>TO</td><td>2</td></tr>\n",
+       "    <tr><td class='row_index'>4</td><td>NewsArticles-1728</td><td>4</td><td>support</td><td>VB</td><td>7</td></tr>\n",
+       "    <tr><td class='row_index'>5</td><td>NewsArticles-1728</td><td>5</td><td>'victims</td><td>NNS</td><td>8</td></tr>\n",
+       "    <tr><td class='row_index'>6</td><td>NewsArticles-1728</td><td>6</td><td>of</td><td>IN</td><td>2</td></tr>\n",
+       "    <tr><td class='row_index'>7</td><td>NewsArticles-1728</td><td>7</td><td>immigrant</td><td>JJ</td><td>9</td></tr>\n",
+       "    <tr><td class='row_index'>8</td><td>NewsArticles-1728</td><td>8</td><td>crimes'</td><td>NN</td><td>7</td></tr>\n",
+       "    <tr><td class='row_index'>9</td><td>NewsArticles-1728</td><td>9</td><td>In</td><td>IN</td><td>2</td></tr>\n",
+       "    <tr><td class='row_index'>10</td><td>NewsArticles-1728</td><td>10</td><td>first</td><td>JJ</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>11</td><td>NewsArticles-1728</td><td>11</td><td>speech</td><td>NN</td><td>6</td></tr>\n",
+       "    <tr><td class='row_index'>12</td><td>NewsArticles-1728</td><td>12</td><td>to</td><td>TO</td><td>2</td></tr>\n",
+       "    <tr><td class='row_index'>13</td><td>NewsArticles-1728</td><td>13</td><td>Congress</td><td>NNP</td><td>8</td></tr>\n",
+       "    <tr><td class='row_index'>14</td><td>NewsArticles-1728</td><td>14</td><td>,</td><td>,</td><td>1</td></tr>\n",
        "    <tr><td class='row_index'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td></tr>\n",
-       "    <tr><td class='row_index'>2570</td><td>NewsArticles-948</td><td>332</td><td>.</td><td>1</td><td>.</td></tr>\n",
-       "    <tr><td class='row_index'>2571</td><td>NewsArticles-948</td><td>333</td><td>Source</td><td>6</td><td>NN</td></tr>\n",
-       "    <tr><td class='row_index'>2572</td><td>NewsArticles-948</td><td>334</td><td>:</td><td>1</td><td>:</td></tr>\n",
-       "    <tr><td class='row_index'>2573</td><td>NewsArticles-948</td><td>335</td><td>-News</td><td>5</td><td>NN</td></tr>\n",
-       "    <tr><td class='row_index'>2574</td><td>NewsArticles-948</td><td>336</td><td>agencies</td><td>8</td><td>NNS</td></tr>\n",
+       "    <tr><td class='row_index'>2570</td><td>NewsArticles-948</td><td>332</td><td>.</td><td>.</td><td>1</td></tr>\n",
+       "    <tr><td class='row_index'>2571</td><td>NewsArticles-948</td><td>333</td><td>Source</td><td>NN</td><td>6</td></tr>\n",
+       "    <tr><td class='row_index'>2572</td><td>NewsArticles-948</td><td>334</td><td>:</td><td>:</td><td>1</td></tr>\n",
+       "    <tr><td class='row_index'>2573</td><td>NewsArticles-948</td><td>335</td><td>-News</td><td>NN</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>2574</td><td>NewsArticles-948</td><td>336</td><td>agencies</td><td>NNS</td><td>8</td></tr>\n",
        "  </tbody>\n",
        "  </table>\n",
        "  <div class='footer'>\n",
@@ -4223,31 +4223,31 @@
        "<div class='datatable'>\n",
        "  <table class='frame'>\n",
        "  <thead>\n",
-       "    <tr class='colnames'><td class='row_index'></td><th>token</th><th>meta_length</th><th>meta_pos</th></tr>\n",
-       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td></tr>\n",
+       "    <tr class='colnames'><td class='row_index'></td><th>token</th><th>meta_pos</th><th>meta_length</th></tr>\n",
+       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td></tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
-       "    <tr><td class='row_index'>0</td><td>Ex-footballer</td><td>13</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>1</td><td>Adam</td><td>4</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>2</td><td>Johnson</td><td>7</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>3</td><td>loses</td><td>5</td><td>VBZ</td></tr>\n",
-       "    <tr><td class='row_index'>4</td><td>appeal</td><td>6</td><td>JJ</td></tr>\n",
-       "    <tr><td class='row_index'>5</td><td>Ex-England</td><td>10</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>6</td><td>footballer</td><td>10</td><td>NN</td></tr>\n",
-       "    <tr><td class='row_index'>7</td><td>Adam</td><td>4</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>8</td><td>Johnson</td><td>7</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>9</td><td>has</td><td>3</td><td>VBZ</td></tr>\n",
-       "    <tr><td class='row_index'>10</td><td>lost</td><td>4</td><td>VBN</td></tr>\n",
-       "    <tr><td class='row_index'>11</td><td>a</td><td>1</td><td>DT</td></tr>\n",
-       "    <tr><td class='row_index'>12</td><td>Court</td><td>5</td><td>NNP</td></tr>\n",
-       "    <tr><td class='row_index'>13</td><td>of</td><td>2</td><td>IN</td></tr>\n",
-       "    <tr><td class='row_index'>14</td><td>Appeal</td><td>6</td><td>NNP</td></tr>\n",
+       "    <tr><td class='row_index'>0</td><td>Ex-footballer</td><td>NNP</td><td>13</td></tr>\n",
+       "    <tr><td class='row_index'>1</td><td>Adam</td><td>NNP</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>2</td><td>Johnson</td><td>NNP</td><td>7</td></tr>\n",
+       "    <tr><td class='row_index'>3</td><td>loses</td><td>VBZ</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>4</td><td>appeal</td><td>JJ</td><td>6</td></tr>\n",
+       "    <tr><td class='row_index'>5</td><td>Ex-England</td><td>NNP</td><td>10</td></tr>\n",
+       "    <tr><td class='row_index'>6</td><td>footballer</td><td>NN</td><td>10</td></tr>\n",
+       "    <tr><td class='row_index'>7</td><td>Adam</td><td>NNP</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>8</td><td>Johnson</td><td>NNP</td><td>7</td></tr>\n",
+       "    <tr><td class='row_index'>9</td><td>has</td><td>VBZ</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>10</td><td>lost</td><td>VBN</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>11</td><td>a</td><td>DT</td><td>1</td></tr>\n",
+       "    <tr><td class='row_index'>12</td><td>Court</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>13</td><td>of</td><td>IN</td><td>2</td></tr>\n",
+       "    <tr><td class='row_index'>14</td><td>Appeal</td><td>NNP</td><td>6</td></tr>\n",
        "    <tr><td class='row_index'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td></tr>\n",
-       "    <tr><td class='row_index'>134</td><td>to</td><td>2</td><td>TO</td></tr>\n",
-       "    <tr><td class='row_index'>135</td><td>another</td><td>7</td><td>DT</td></tr>\n",
-       "    <tr><td class='row_index'>136</td><td>sexual</td><td>6</td><td>JJ</td></tr>\n",
-       "    <tr><td class='row_index'>137</td><td>act</td><td>3</td><td>NN</td></tr>\n",
-       "    <tr><td class='row_index'>138</td><td>.</td><td>1</td><td>.</td></tr>\n",
+       "    <tr><td class='row_index'>134</td><td>to</td><td>TO</td><td>2</td></tr>\n",
+       "    <tr><td class='row_index'>135</td><td>another</td><td>DT</td><td>7</td></tr>\n",
+       "    <tr><td class='row_index'>136</td><td>sexual</td><td>JJ</td><td>6</td></tr>\n",
+       "    <tr><td class='row_index'>137</td><td>act</td><td>NN</td><td>3</td></tr>\n",
+       "    <tr><td class='row_index'>138</td><td>.</td><td>.</td><td>1</td></tr>\n",
        "  </tbody>\n",
        "  </table>\n",
        "  <div class='footer'>\n",
@@ -4284,31 +4284,31 @@
        "<div class='datatable'>\n",
        "  <table class='frame'>\n",
        "  <thead>\n",
-       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_length</th><th>meta_pos</th><th>meta_small_nouns</th></tr>\n",
-       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='boolean' title='bool8'>&#x25AA;</td></tr>\n",
+       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_small_nouns</th><th>meta_pos</th><th>meta_length</th></tr>\n",
+       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='boolean' title='bool8'>&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td></tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
-       "    <tr><td class='row_index'>0</td><td>NewsArticles-1728</td><td>0</td><td>Trump</td><td>5</td><td>NN</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>1</td><td>NewsArticles-1728</td><td>1</td><td>:</td><td>1</td><td>:</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>2</td><td>NewsArticles-1728</td><td>2</td><td>Agency</td><td>6</td><td>NN</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>3</td><td>NewsArticles-1728</td><td>3</td><td>to</td><td>2</td><td>TO</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>4</td><td>NewsArticles-1728</td><td>4</td><td>support</td><td>7</td><td>VB</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>5</td><td>NewsArticles-1728</td><td>5</td><td>'victims</td><td>8</td><td>NNS</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>6</td><td>NewsArticles-1728</td><td>6</td><td>of</td><td>2</td><td>IN</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>7</td><td>NewsArticles-1728</td><td>7</td><td>immigrant</td><td>9</td><td>JJ</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>8</td><td>NewsArticles-1728</td><td>8</td><td>crimes'</td><td>7</td><td>NN</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>9</td><td>NewsArticles-1728</td><td>9</td><td>In</td><td>2</td><td>IN</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>10</td><td>NewsArticles-1728</td><td>10</td><td>first</td><td>5</td><td>JJ</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>11</td><td>NewsArticles-1728</td><td>11</td><td>speech</td><td>6</td><td>NN</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>12</td><td>NewsArticles-1728</td><td>12</td><td>to</td><td>2</td><td>TO</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>13</td><td>NewsArticles-1728</td><td>13</td><td>Congress</td><td>8</td><td>NNP</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>14</td><td>NewsArticles-1728</td><td>14</td><td>,</td><td>1</td><td>,</td><td>0</td></tr>\n",
+       "    <tr><td class='row_index'>0</td><td>NewsArticles-1728</td><td>0</td><td>Trump</td><td>1</td><td>NN</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>1</td><td>NewsArticles-1728</td><td>1</td><td>:</td><td>0</td><td>:</td><td>1</td></tr>\n",
+       "    <tr><td class='row_index'>2</td><td>NewsArticles-1728</td><td>2</td><td>Agency</td><td>0</td><td>NN</td><td>6</td></tr>\n",
+       "    <tr><td class='row_index'>3</td><td>NewsArticles-1728</td><td>3</td><td>to</td><td>0</td><td>TO</td><td>2</td></tr>\n",
+       "    <tr><td class='row_index'>4</td><td>NewsArticles-1728</td><td>4</td><td>support</td><td>0</td><td>VB</td><td>7</td></tr>\n",
+       "    <tr><td class='row_index'>5</td><td>NewsArticles-1728</td><td>5</td><td>'victims</td><td>0</td><td>NNS</td><td>8</td></tr>\n",
+       "    <tr><td class='row_index'>6</td><td>NewsArticles-1728</td><td>6</td><td>of</td><td>0</td><td>IN</td><td>2</td></tr>\n",
+       "    <tr><td class='row_index'>7</td><td>NewsArticles-1728</td><td>7</td><td>immigrant</td><td>0</td><td>JJ</td><td>9</td></tr>\n",
+       "    <tr><td class='row_index'>8</td><td>NewsArticles-1728</td><td>8</td><td>crimes'</td><td>0</td><td>NN</td><td>7</td></tr>\n",
+       "    <tr><td class='row_index'>9</td><td>NewsArticles-1728</td><td>9</td><td>In</td><td>0</td><td>IN</td><td>2</td></tr>\n",
+       "    <tr><td class='row_index'>10</td><td>NewsArticles-1728</td><td>10</td><td>first</td><td>0</td><td>JJ</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>11</td><td>NewsArticles-1728</td><td>11</td><td>speech</td><td>0</td><td>NN</td><td>6</td></tr>\n",
+       "    <tr><td class='row_index'>12</td><td>NewsArticles-1728</td><td>12</td><td>to</td><td>0</td><td>TO</td><td>2</td></tr>\n",
+       "    <tr><td class='row_index'>13</td><td>NewsArticles-1728</td><td>13</td><td>Congress</td><td>0</td><td>NNP</td><td>8</td></tr>\n",
+       "    <tr><td class='row_index'>14</td><td>NewsArticles-1728</td><td>14</td><td>,</td><td>0</td><td>,</td><td>1</td></tr>\n",
        "    <tr><td class='row_index'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td></tr>\n",
-       "    <tr><td class='row_index'>2570</td><td>NewsArticles-948</td><td>332</td><td>.</td><td>1</td><td>.</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>2571</td><td>NewsArticles-948</td><td>333</td><td>Source</td><td>6</td><td>NN</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>2572</td><td>NewsArticles-948</td><td>334</td><td>:</td><td>1</td><td>:</td><td>0</td></tr>\n",
-       "    <tr><td class='row_index'>2573</td><td>NewsArticles-948</td><td>335</td><td>-News</td><td>5</td><td>NN</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>2574</td><td>NewsArticles-948</td><td>336</td><td>agencies</td><td>8</td><td>NNS</td><td>0</td></tr>\n",
+       "    <tr><td class='row_index'>2570</td><td>NewsArticles-948</td><td>332</td><td>.</td><td>0</td><td>.</td><td>1</td></tr>\n",
+       "    <tr><td class='row_index'>2571</td><td>NewsArticles-948</td><td>333</td><td>Source</td><td>0</td><td>NN</td><td>6</td></tr>\n",
+       "    <tr><td class='row_index'>2572</td><td>NewsArticles-948</td><td>334</td><td>:</td><td>0</td><td>:</td><td>1</td></tr>\n",
+       "    <tr><td class='row_index'>2573</td><td>NewsArticles-948</td><td>335</td><td>-News</td><td>1</td><td>NN</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>2574</td><td>NewsArticles-948</td><td>336</td><td>agencies</td><td>0</td><td>NNS</td><td>8</td></tr>\n",
        "  </tbody>\n",
        "  </table>\n",
        "  <div class='footer'>\n",
@@ -4360,31 +4360,31 @@
        "<div class='datatable'>\n",
        "  <table class='frame'>\n",
        "  <thead>\n",
-       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_length</th><th>meta_pos</th><th>meta_small_nouns</th></tr>\n",
-       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='boolean' title='bool8'>&#x25AA;</td></tr>\n",
+       "    <tr class='colnames'><td class='row_index'></td><th>doc</th><th>position</th><th>token</th><th>meta_small_nouns</th><th>meta_pos</th><th>meta_length</th></tr>\n",
+       "    <tr class='coltypes'><td class='row_index'></td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int64'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='boolean' title='bool8'>&#x25AA;</td><td class='string' title='str32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td><td class='integer' title='int32'>&#x25AA;&#x25AA;&#x25AA;&#x25AA;</td></tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
-       "    <tr><td class='row_index'>0</td><td>NewsArticles-1728</td><td>0</td><td>Trump</td><td>5</td><td>NN</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>1</td><td>NewsArticles-1728</td><td>1</td><td>Path</td><td>4</td><td>NN</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>2</td><td>NewsArticles-1728</td><td>2</td><td>wall'</td><td>5</td><td>NN</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>3</td><td>NewsArticles-1728</td><td>3</td><td>Trump</td><td>5</td><td>NNP</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>4</td><td>NewsArticles-1728</td><td>4</td><td>crime</td><td>5</td><td>NN</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>5</td><td>NewsArticles-1728</td><td>5</td><td>VOICE</td><td>5</td><td>NN</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>6</td><td>NewsArticles-1728</td><td>6</td><td>Crime</td><td>5</td><td>NNP</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>7</td><td>NewsArticles-1728</td><td>7</td><td>VOICE</td><td>5</td><td>NNP</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>8</td><td>NewsArticles-1728</td><td>8</td><td>list</td><td>4</td><td>NN</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>9</td><td>NewsArticles-1728</td><td>9</td><td>US</td><td>2</td><td>NNP</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>10</td><td>NewsArticles-1728</td><td>10</td><td>name</td><td>4</td><td>NN</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>11</td><td>NewsArticles-1728</td><td>11</td><td>Trump</td><td>5</td><td>NNP</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>12</td><td>NewsArticles-1728</td><td>12</td><td>name</td><td>4</td><td>NN</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>13</td><td>NewsArticles-1728</td><td>13</td><td>READ</td><td>4</td><td>NNP</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>14</td><td>NewsArticles-1728</td><td>14</td><td>Trump</td><td>5</td><td>NNP</td><td>1</td></tr>\n",
+       "    <tr><td class='row_index'>0</td><td>NewsArticles-1728</td><td>0</td><td>Trump</td><td>1</td><td>NN</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>1</td><td>NewsArticles-1728</td><td>1</td><td>Path</td><td>1</td><td>NN</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>2</td><td>NewsArticles-1728</td><td>2</td><td>wall'</td><td>1</td><td>NN</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>3</td><td>NewsArticles-1728</td><td>3</td><td>Trump</td><td>1</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>4</td><td>NewsArticles-1728</td><td>4</td><td>crime</td><td>1</td><td>NN</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>5</td><td>NewsArticles-1728</td><td>5</td><td>VOICE</td><td>1</td><td>NN</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>6</td><td>NewsArticles-1728</td><td>6</td><td>Crime</td><td>1</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>7</td><td>NewsArticles-1728</td><td>7</td><td>VOICE</td><td>1</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>8</td><td>NewsArticles-1728</td><td>8</td><td>list</td><td>1</td><td>NN</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>9</td><td>NewsArticles-1728</td><td>9</td><td>US</td><td>1</td><td>NNP</td><td>2</td></tr>\n",
+       "    <tr><td class='row_index'>10</td><td>NewsArticles-1728</td><td>10</td><td>name</td><td>1</td><td>NN</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>11</td><td>NewsArticles-1728</td><td>11</td><td>Trump</td><td>1</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>12</td><td>NewsArticles-1728</td><td>12</td><td>name</td><td>1</td><td>NN</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>13</td><td>NewsArticles-1728</td><td>13</td><td>READ</td><td>1</td><td>NNP</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>14</td><td>NewsArticles-1728</td><td>14</td><td>Trump</td><td>1</td><td>NNP</td><td>5</td></tr>\n",
        "    <tr><td class='row_index'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td><td class='hellipsis'>&#x22EE;</td></tr>\n",
-       "    <tr><td class='row_index'>254</td><td>NewsArticles-948</td><td>40</td><td>flow</td><td>4</td><td>NN</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>255</td><td>NewsArticles-948</td><td>41</td><td>goods</td><td>5</td><td>NNS</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>256</td><td>NewsArticles-948</td><td>42</td><td>Egypt</td><td>5</td><td>NNP</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>257</td><td>NewsArticles-948</td><td>43</td><td>Gaza</td><td>4</td><td>NNP</td><td>1</td></tr>\n",
-       "    <tr><td class='row_index'>258</td><td>NewsArticles-948</td><td>44</td><td>-News</td><td>5</td><td>NN</td><td>1</td></tr>\n",
+       "    <tr><td class='row_index'>254</td><td>NewsArticles-948</td><td>40</td><td>flow</td><td>1</td><td>NN</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>255</td><td>NewsArticles-948</td><td>41</td><td>goods</td><td>1</td><td>NNS</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>256</td><td>NewsArticles-948</td><td>42</td><td>Egypt</td><td>1</td><td>NNP</td><td>5</td></tr>\n",
+       "    <tr><td class='row_index'>257</td><td>NewsArticles-948</td><td>43</td><td>Gaza</td><td>1</td><td>NNP</td><td>4</td></tr>\n",
+       "    <tr><td class='row_index'>258</td><td>NewsArticles-948</td><td>44</td><td>-News</td><td>1</td><td>NN</td><td>5</td></tr>\n",
        "  </tbody>\n",
        "  </table>\n",
        "  <div class='footer'>\n",
diff --git a/doc/source/text_corpora.ipynb b/doc/source/text_corpora.ipynb
index 8723917..c66462c 100644
--- a/doc/source/text_corpora.ipynb
+++ b/doc/source/text_corpora.ipynb
@@ -197,6 +197,12 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "sample2 :\n",
+      "Here comes the second example.\n",
+      "\n",
+      "This one contains three lines of plain text which means two paragraphs.\n",
+      "---\n",
+      "\n",
       "sample1 :\n",
       "This is the first example file. ☺\n",
       "---\n",
@@ -210,12 +216,6 @@
       "\n",
       "The third and final paragraph.\n",
       "---\n",
-      "\n",
-      "sample2 :\n",
-      "Here comes the second example.\n",
-      "\n",
-      "This one contains three lines of plain text which means two paragraphs.\n",
-      "---\n",
       "\n"
      ]
     }
diff --git a/doc/source/topic_modeling.ipynb b/doc/source/topic_modeling.ipynb
index f363b5b..b56757a 100644
--- a/doc/source/topic_modeling.ipynb
+++ b/doc/source/topic_modeling.ipynb
@@ -336,11 +336,11 @@
        "            {'smaller': [({'n_topics': 10,\n",
        "                'n_iter': 1000,\n",
        "                'random_state': 20191122},\n",
-       "               <lda.lda.LDA at 0x7fc42d183630>)],\n",
+       "               <lda.lda.LDA at 0x7f4251b0aef0>)],\n",
        "             'bigger': [({'n_topics': 10,\n",
        "                'n_iter': 1000,\n",
        "                'random_state': 20191122},\n",
-       "               <lda.lda.LDA at 0x7fc42d183978>)]})"
+       "               <lda.lda.LDA at 0x7f4251b0a828>)]})"
       ]
      },
      "execution_count": 8,
@@ -397,7 +397,7 @@
      "data": {
       "text/plain": [
        "[({'n_topics': 10, 'n_iter': 1000, 'random_state': 20191122},\n",
-       "  <lda.lda.LDA at 0x7fc42d183630>)]"
+       "  <lda.lda.LDA at 0x7f4251b0aef0>)]"
       ]
      },
      "execution_count": 9,
@@ -561,14 +561,14 @@
     {
      "data": {
       "text/plain": [
-       "[({'alpha': 0.1, 'n_iter': 500, 'n_topics': 10, 'random_state': 20191122},\n",
-       "  <lda.lda.LDA at 0x7fc430c02ef0>),\n",
+       "[({'alpha': 0.001, 'n_iter': 500, 'n_topics': 10, 'random_state': 20191122},\n",
+       "  <lda.lda.LDA at 0x7f423661ffd0>),\n",
        " ({'alpha': 0.01, 'n_iter': 500, 'n_topics': 10, 'random_state': 20191122},\n",
-       "  <lda.lda.LDA at 0x7fc430c02978>),\n",
-       " ({'alpha': 0.001, 'n_iter': 500, 'n_topics': 10, 'random_state': 20191122},\n",
-       "  <lda.lda.LDA at 0x7fc42d19bdd8>),\n",
+       "  <lda.lda.LDA at 0x7f4251af5eb8>),\n",
+       " ({'alpha': 0.1, 'n_iter': 500, 'n_topics': 10, 'random_state': 20191122},\n",
+       "  <lda.lda.LDA at 0x7f4251af5e10>),\n",
        " ({'alpha': 0.0001, 'n_iter': 500, 'n_topics': 10, 'random_state': 20191122},\n",
-       "  <lda.lda.LDA at 0x7fc42d19bd30>)]"
+       "  <lda.lda.LDA at 0x7f4251af5d30>)]"
       ]
      },
      "execution_count": 12,
@@ -736,16 +736,16 @@
        "   'n_iter': 1000,\n",
        "   'eta': 0.1,\n",
        "   'random_state': 20191122},\n",
-       "  {'model': <lda.lda.LDA at 0x7fc42d19bcf8>,\n",
+       "  {'model': <lda.lda.LDA at 0x7f4251af5cf8>,\n",
        "   'cao_juan_2009': 0.11481331353994903,\n",
-       "   'arun_2010': 10.81440771487237,\n",
+       "   'arun_2010': 10.814407714872376,\n",
        "   'coherence_mimno_2011': -1.5705955029901921}),\n",
        " ({'n_topics': 30,\n",
        "   'alpha': 0.03333333333333333,\n",
        "   'n_iter': 1000,\n",
        "   'eta': 0.1,\n",
        "   'random_state': 20191122},\n",
-       "  {'model': <lda.lda.LDA at 0x7fc42d23d4a8>,\n",
+       "  {'model': <lda.lda.LDA at 0x7f422b9d24a8>,\n",
        "   'cao_juan_2009': 0.11299796966131251,\n",
        "   'arun_2010': 6.3501538041085475,\n",
        "   'coherence_mimno_2011': -1.5797425879990783}),\n",
@@ -754,7 +754,7 @@
        "   'n_iter': 1000,\n",
        "   'eta': 0.1,\n",
        "   'random_state': 20191122},\n",
-       "  {'model': <lda.lda.LDA at 0x7fc42d23d518>,\n",
+       "  {'model': <lda.lda.LDA at 0x7f422b9bf128>,\n",
        "   'cao_juan_2009': 0.11013624472342246,\n",
        "   'arun_2010': 4.853368419225177,\n",
        "   'coherence_mimno_2011': -1.6514230985163838})]"
@@ -804,17 +804,17 @@
      "data": {
       "text/plain": [
        "[(20,\n",
-       "  {'model': <lda.lda.LDA at 0x7fc42d19bcf8>,\n",
+       "  {'model': <lda.lda.LDA at 0x7f4251af5cf8>,\n",
        "   'cao_juan_2009': 0.11481331353994903,\n",
-       "   'arun_2010': 10.81440771487237,\n",
+       "   'arun_2010': 10.814407714872376,\n",
        "   'coherence_mimno_2011': -1.5705955029901921}),\n",
        " (30,\n",
-       "  {'model': <lda.lda.LDA at 0x7fc42d23d4a8>,\n",
+       "  {'model': <lda.lda.LDA at 0x7f422b9d24a8>,\n",
        "   'cao_juan_2009': 0.11299796966131251,\n",
        "   'arun_2010': 6.3501538041085475,\n",
        "   'coherence_mimno_2011': -1.5797425879990783}),\n",
        " (40,\n",
-       "  {'model': <lda.lda.LDA at 0x7fc42d23d518>,\n",
+       "  {'model': <lda.lda.LDA at 0x7f422b9bf128>,\n",
        "   'cao_juan_2009': 0.11013624472342246,\n",
        "   'arun_2010': 4.853368419225177,\n",
        "   'coherence_mimno_2011': -1.6514230985163838})]"
@@ -848,7 +848,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 576x432 with 3 Axes>"
       ]
@@ -1039,13 +1039,21 @@
        "</div>"
       ],
       "text/plain": [
-       "                             rank_1             rank_2         rank_3          rank_4           rank_5             rank_6  \\\n",
-       "topic                                                                                                                       \n",
-       "10_recall_vehicle  recall (0.07373)  vehicle (0.05172)  car (0.03338)  2015 (0.02605)  cause (0.02605)  company (0.02605)   \n",
+       "                             rank_1             rank_2         rank_3  \\\n",
+       "topic                                                                   \n",
+       "10_recall_vehicle  recall (0.07373)  vehicle (0.05172)  car (0.03338)   \n",
        "\n",
-       "                              rank_7          rank_8          rank_9          rank_10  \n",
-       "topic                                                                                  \n",
-       "10_recall_vehicle  include (0.02605)  2014 (0.02605)  fire (0.01871)  level (0.01504)  "
+       "                           rank_4           rank_5             rank_6  \\\n",
+       "topic                                                                   \n",
+       "10_recall_vehicle  2015 (0.02605)  cause (0.02605)  company (0.02605)   \n",
+       "\n",
+       "                              rank_7          rank_8          rank_9  \\\n",
+       "topic                                                                  \n",
+       "10_recall_vehicle  include (0.02605)  2014 (0.02605)  fire (0.01871)   \n",
+       "\n",
+       "                           rank_10  \n",
+       "topic                               \n",
+       "10_recall_vehicle  level (0.01504)  "
       ]
      },
      "execution_count": 21,
@@ -2126,11 +2134,17 @@
        "</div>"
       ],
       "text/plain": [
-       "                       rank_1                rank_2               rank_3           rank_4               rank_5\n",
-       "topic                                                                                                         \n",
-       "topic_1      record (-0.2566)        rock (-0.6573)       best (-0.7433)    list (-1.149)        mike (-1.162)\n",
-       "topic_2  referendum (-0.4418)        vote (-0.4827)  government (-1.178)    street (-1.2)        next (-1.286)\n",
-       "topic_3         car (-0.8822)  reportedly (-0.9954)       white (-1.008)  vehicle (-1.08)  individual (-1.198)"
+       "                       rank_1                rank_2               rank_3  \\\n",
+       "topic                                                                      \n",
+       "topic_1      record (-0.2566)        rock (-0.6573)       best (-0.7433)   \n",
+       "topic_2  referendum (-0.4418)        vote (-0.4827)  government (-1.178)   \n",
+       "topic_3         car (-0.8822)  reportedly (-0.9954)       white (-1.008)   \n",
+       "\n",
+       "                  rank_4               rank_5  \n",
+       "topic                                          \n",
+       "topic_1    list (-1.149)        mike (-1.162)  \n",
+       "topic_2    street (-1.2)        next (-1.286)  \n",
+       "topic_3  vehicle (-1.08)  individual (-1.198)  "
       ]
      },
      "execution_count": 50,
@@ -2229,13 +2243,21 @@
        "</div>"
       ],
       "text/plain": [
-       "                                        rank_1                      rank_2                           rank_3\n",
-       "document                                                                                                   \n",
-       "NewsArticles-1041      22_south_visit (0.8199)  15_campaign_news (0.06708)  34_president_security (0.06192)\n",
-       "NewsArticles-1065    27_china_chinese (0.4759)  35_election_party (0.3074)           40_father_new (0.1389)\n",
-       "NewsArticles-1099  25_trump_president (0.3958)      8_order_enter (0.3464)       12_ryan_democrats (0.2104)\n",
-       "NewsArticles-1169       33_kill_group (0.4507)   47_russia_border (0.1984)       37_board_solution (0.1398)\n",
-       "NewsArticles-1174       33_kill_group (0.6924)   3_car_reportedly (0.2984)      49_hospital_care (0.000213)"
+       "                                        rank_1                      rank_2  \\\n",
+       "document                                                                     \n",
+       "NewsArticles-1041      22_south_visit (0.8199)  15_campaign_news (0.06708)   \n",
+       "NewsArticles-1065    27_china_chinese (0.4759)  35_election_party (0.3074)   \n",
+       "NewsArticles-1099  25_trump_president (0.3958)      8_order_enter (0.3464)   \n",
+       "NewsArticles-1169       33_kill_group (0.4507)   47_russia_border (0.1984)   \n",
+       "NewsArticles-1174       33_kill_group (0.6924)   3_car_reportedly (0.2984)   \n",
+       "\n",
+       "                                            rank_3  \n",
+       "document                                            \n",
+       "NewsArticles-1041  34_president_security (0.06192)  \n",
+       "NewsArticles-1065           40_father_new (0.1389)  \n",
+       "NewsArticles-1099       12_ryan_democrats (0.2104)  \n",
+       "NewsArticles-1169       37_board_solution (0.1398)  \n",
+       "NewsArticles-1174      49_hospital_care (0.000213)  "
       ]
      },
      "execution_count": 51,
@@ -2725,9 +2747,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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EH1NPY2ALrrEAOT8ug6IWjG7BNfPyfXre9/0itNq7tOyOGO1HnABZHfleTGpRX9LSGxiCNjaXRoPUeOSt3Q6mrc1kvu/10kQH3du4BX0BbdjuiqIULA9MbtF1s3AaWnU3mwXIx2cc8ueZBcxGz24JpFZaGn2/1yS7GrARLgHeQs6chpGaOAEyA4WcqAqDge8gP4GlQ85PR+aWP0WhVHoifoGxIZ4vT5BDWtAXgNuQAOkFfJ3WDNBZOBT4eZPangz8G1nVPYl8mebH1qhnRWA7ZJ22P7IMK5reyEH104T7HRlGw4xCnsNV2Eg8nORQGO4xGzi2nG7mYjDePWQNlX6Ur41/RJTZFn1GrfADGYCC+9VQ2I+DEspvBSyXsu2i2JD03620x1wUlXoXivesXxNt8ufN1Bl2vEUFYic5jMT8QIZRcT+QOLZCy+vjy+qAw0F4oTBq6Md+D/An4DfImuQ+tALxf3BfLKOzORhMfgHSH5joa+ceFCF2Z/Rl/A0SHhPQ6jKtAOmDQvS77Z5H+oizu1Ef+uMulIjsSKdvp6Fn+ZZzfrOU7RbBABQavUjBcTGwUgv63hcZJkwusP814I8t6HsaRmICZBhtLEBAM6hxKPfA9kiP3SfmKJqBeD+QaUgNEjVwLYnyhkz3lR8UUbaKDCa/AAHlophJ9BdqElKJ3EO0ANkaDazvIVVm3ID5EfAmEipR7IyXhjjp2CjLTWfkryn7lOa4CznftprlUTK3IoXIvi29g3BGYgJkGG0sQG5EeltXBZHmKJoznXYXkT5J1S544U/ObkKfmsVgihEgoDTEv0fBLGcjgfIq0vO7sZx+S7QA2ZXGv6gjE/q0BHAiiqf2HhI+bkj3u9GzaqXwOIhiBtt5wOmUr+o9keKCPI4nfJ+xlYzEBMgw2liAZOls0TzqtHtbg/Vuceo9WnSHjI5gAArGmffHOYNqzNZdDqK4EPNlGzyMxATIMCouQHrFnFsyw1E06zt/72uw3v3O3w2K64rRQVxA/vhWM1BsqSqZvt6KDE6KmMyNoHPT5RoFESdA5mQ4isZdRn/SYL2pgfpp2QH9+J5tsF5RdCG14ThaEzW12ddzLbdebULbWRkKfCNnGwvQQP1Y/u4Uziji96PS0p/2UgEbJRAnQKqA69fQqFWLWz7Kka6qDAR2RE6cQxqoNxTYvIXXa2fOIb9p7RnIt6OqnIvypOfla+i7YRihVF2AuE5N+zVY77PO3xcK7EsrmILCbL+FvLjTcgXwfy28XrsyhPwpBu5CnttVpoYsFhtxWAxjMSREDCOUqgsQd/N8Z+DLKet8BfiM8/rmwnvUXGookdR6pF89LYt8dlp1vXbmB+SzlpqFnFSbYTBSNC9RjE/H16h+1G6jJOIEyAXICiANx5N/ZhfGFSjREMhh8Nd4G+tBNkQB4a5w/h/j1MlCFXKhpGVvqj8RqAIbo5AlefgFMnFtF36O9mvysArpxwHD+B81vME4iWeIzziXh6Ancw2FcRiNrLMeo7uvygyyzcrdTfTH0Mz+t2iDeS5yljuHaEfGJZy6Nzr/b4U2NCciX4w3iDaNnEJ387vBMf3cGZkqjw2pl8YUs9HruSwNfBt4CjkkzkKC+j8ofW0w8J+7if4iMie8CKnL5iIH0VE0J7ZTGJeQzxxyItUJ89EIRThL/rPlvTYzXmgDM96ilqaTaF4q0vvQHsi1eJvjKxNtYvg2spB5Osc1FwMeBNZBg+Xb6P5+iDad9yU68u8qyJnx38h67Dk0sG5GtGf8qSj3/CDgBGDxhP71RZ/53cCmSPC9Rvc0uE8WdD2Q8HgcrfQmI6HQCwmevdA9R4VFmY9ynW+NLNzeRfsRBzl1t6e5+1WLodApefgDmpi0G1cDR+RsYw+qkSXSaCMaWYHcR/4NuyQGomi8z1AfG6vmXPtRFMokjz+KuwKpocHSP+APxpvxnxJS112BfIhWLcdTr28fRLpZ/iTSrwhA9vqNPKus1zsJbzYaTEi1AeHqIX8Axg+pX20MQBvSNdIHdMzKMPLN4ubhefC3G32oj4+W9UgKhFk0I3P211YgLViBxJF2UFoDxZ8a19zu1NEfxR0aCqxNcU6MfgHy6ZDzRzjnXg455wqQPIM5VFeAnOuUO7OBtv0CJMwIwv28JzTQZhZuId+P8JYm96/ZXE3+geiyFvd5ZM7+mgBpgQDxq7A2p7sp6E7ED0zLAHuiTl5dbNdimYl06c1iFuEZ9G5HD2VjtKKISrZ1eZP6VSZubpHT0H7OTaQ3NljklA/iOhg202lyGTyz7qzcUERHSuQBFOo/D1UK2WJUBL8A6UIz+q3wrHo2dI4kRqN0oJ3Ce4QPjtOROmBFtPKJEiBvNqlfZXIHMgs9ASXuehe4EgnLpNXnBCT0g7jRC4rOmeFnD/LlgJ9D47HYqsYDBbSxBtqD/LCAtowOwS9AnkPJhpZFpqHXI8EQN/uajezNH0Ez804hLiyLu5HYP6bM1Jhz7cyJyKrnTLT5fTbwPSRIvk20L0mY8GgVe+esP5r23Dz38yZ6BnHf2TRsg1bhhgGEW2F9goTGT5FwuLiVHSqQ+5FqbZsMdeP2VNwfYZmDYpk84BzrIkOBE4DjgE+h1evc8roWyl45699XSC/KpYbUhVvnbMcEiFFHnAPas63qRBPoQt7oWX8wqxOuVlkaWMF5PSZj253CW8gqbgM0OG0CHFZqj7qzHjLFzkMR6p8qEGb40Sh5BZDRYcQJkF/SfPPKZjGAfN7ZS6CkSkEOdP6+TPT+R6uZ7fxdpqTrf4RnpbRWSX2IYpcC2miWg2yrKcLSbb0C2jA6iLhB9kHa1xSuiGxqv6Le9n8w8GPn9e8LaL8o3ICTe5I/x0UcxyCrvGAsqdWAQ5zXVQteuUXO+u8ir/1OoIjN72Z+v4w2pFODpOWdjd+KYm69DTyBLLJ2QB7b9yCv5KI4FM3slkb9du22z0OzxmnOcTnh+wuPoI3eHdDK6EkU/2gQEnRB+/2s1zsS2AcNqGORNdpyyHKvD/K8r5q1UpYQ936qJhDzUIQAGYAceqcU0JbRAVRBgKwDfBENeleiOFcuB2RsM28mwlHAP9Cgegja9xgPXAP8hPwB6vx8m/AwMEcH/r+ecAFSQ34OP0Iqtp2QWmsM4YNG1uv9Apkxb4VMuzd3/n8MuA4JqqpZ4uUVIJ20z1WU0ccamAAxUjIEDSQT0KCZ5PWYhdd99YP65rxemFUb0IzWsRb5vzvfbnmvm8e+FPN7apVD4cic/WxX9bufYbSRJ3qQLZF6pBm5zv0s53u9WpOvZfQcNi2gjXYK3Z5EUSmn8/qSGB1EnAA5BwmPu5HD2Ks0J+/5MXjBCX8dUeY66lVbSayC1GJGz6WIDd9rncPwaPaE0mgj4gTITihs9yE01xP3dpKdky4AXmmgzSGYAOnp2Gq2OfQruwNGdYgz4x2ArFCqEMahUZ+LTg0lYqRn1bI70KHYCsT4H3ECZDzF+FPkZRGN5+s2AWLYCqQ5RGXkNHogcQLkJuSI1aqUo2E8APyL6Ox/UUynZ1pgjULmmieU3ZEKYCuQ5hB0JDV6MHEC5DyUzvUOlAyoDOuLXfHChzTCIuAdtIfTU1gcZY3rBxxccl+qwMCyO2AYnU7cJvr3kcPQtsjB7y9E53Vw2aiwnuVn7bI70GLmIg/63VHI9Z6OqVoMo8nECZDvBv7vhaLUGs3hOvQZH5GjDVt5eNhmr2E0mTgBsm3LemEsjrxOHy+5H52ErUAMo8nECZAnW9YLYydsxlwkvciXxtYwjBTkyZlhFMdny+5Ah7F42R0wjJ5AFaLxpqEPisy7M7Lv70d6c8KoiL7jnbbWRlFrTwc+j6ID90ZWXLej1L4TI9pYFu1ZfBaFNV8JWYBNRBZsf0Eb20GWB85CZtJDnXZACZDCzI9/Svc9KVCO8rDcJFHlw1gFGAHsh3KeLAaMA+5CEXjfjqhXxOfXLIqMlmwYRgaqEvl2KPBGxv7E9Wm8c/4IFAU4qv44wn0K+qP88UnX/3lI3Q2d67vHTKfs3MD77vG9iHvYDYWdfwjFKnMjJl8Yc99+DsTzmQk75iIT7jDyfn7NJk30aDsaP9JOTPIyMmc/OyEa7+Hkf16lReNthAk0FqsqLYOQH8rKTWjb5Qr0OXwXBc57HwXi+wZwGrI8uwA4NlBvJnK2XA34G/AwSrTUD/gUcAnKS3Iq8Gfqc1K/Rr1F2zXAl4D/Ep5KN4r7nMNlLOnTym4L/B3o61z3TJSYaiGwGTLj/hz6IU9CDp1hZP38ms1s8v145gO/K6gvncQTZXegB9G37A7kYYmYY3mUWOhslL3uzzRnP+VcPEk6ETgDDbDro6x6aY4o3Bl0DTgqoswo53xULK44NdrmvvZPiSkHEiA14P6EckmMddpJswJ5xCn7AtEWSzc5ZcbSfbJRxOfXTD4i38xtfuu73DZsgz6jV5t4jZHYCuRYKr4CKYKdUUe/2YS2n3DankH6mXVa3AEwSscPcBLeg8gSF+x9p+4FCeVaLUDWw7uvYCZCP0N95YIb/a34/PLwDvl/fD3NFHgo6bI4mgBpDSdScQFSxKrhQeBF4KsFtBVkfefvSDQgNIOHYs5N8L3OYmbrppStmrHCp3yvH4gp9xxe+tIdI8o08/PLw/QC2liqgDbaiSuA/yu7E8b/qLxpf1Fqpw+IVxdlxf0AX44tlY8PUpaLUlftCfwKuBel5/0IDV7z0Iyuiqzoe510/+75VRLOJ9HqIHzvFdDGMgW00S4si9TSRnVYvuwOJFHEzLgX2ixuhunkRzQ/fEpWXfcaaBN6O+f/uUid8wraF5oN7EM1QuIHqTVQ1h34o+pUda/g3QLaWBV4s4B22oG9Mb+wqlF5AZL3CzMAuBhYE3g2b2dCcL3hywwpH8WNSHhMBo5E0V83Qb4cByITvLSz81bjTw+cZGLrrjyqei9RjCugjTUz1psDXIS+H68iNaC7D3YQUsdORX42YfRHfkLPI2u/qUjVeHhEeXdP4ifoN3kR8Baa1ExGxgxhv6GdgVvQ3tn1znvH0V2PHrWHt6DB6xmNsVzZHUgibgWStEG2BDJhddu4qJAe1fNnFCPqCJSjvQi1RBGsC2zvvP4+3o/PTy/kWJgGd3bfqhngI77Xu6ABJIwt8VZQ/21mh5pAESuQrAIEtBl9CBpQ10Tfk3eR0HgJqYxORc/iZl+9ldAG8GZI8IxGqtwd0IC/F3A84SvCrZEqdWs0oXsXpXc+yKm3PbK6c+mLLOTuBjZ1rvEaMkn3ExXWaH6D1zMaY4WyO5CHtLv8b5EvgmwSVznXeRF9yYvCtSKKs5Aahneffl+ULXzvHxZR98u+MklWUb91yo0nnxAZm/J6IP+aGtpfCtus60JOim6/gjbpeT6/VrA76b/DUcflGa89x6l/vPP/cOf/BcDXnfcOdd67IlD3duf9v1Kff3x1NEjXkI+NH3cFUkOGG/7Z/wAUVaBG+ETHZUREf8Io4npJjCTfs+sEK6wxVNwKK0803gXIN6PZq4KTkUPhfmhJfx+atb1LfG4Slzxf4ihec67dH/mmPIkeNmhv5GTgW2gzPY0lz6NOndWQSvDH6IfZDw28s6hXOxXBt1D0343RLPJ7eI6EmyIVyjCn7DeRUUA78WIBbWyRs/51zt/bnb81FN4GvFXgOr7yWyFz6Y+QKmmW79x4NCl5DvlfXY5URkHOAJ7x/T/DKb8nWsEUTauv11Pog8YSIwdjUWypPBI4irwz6G8FrvMJ+sG7//8QrQTSrAgWQ4N51D2cHlJnd+Todzfyl3kdL3zHVKQmeRStNG4gPEf4LkjFEnXd+Xgz5iBVX4GA9kHyfHdmk83QZA71zpO90Pd4jO+9JZ1rPOZ77yznvT/FtP2yU2YX33vuimAh4ZlDB+KtgKIYQeMrkDzXS2IkPXsFsg75Vx9NX4FU3epiLaqbg/lXwB5ogB6PfkjT0Wxzb+RFPzplW/NRXKvz0cA/G834P0R+FmGz6Q2QGmQP9INeHwUxBO1bbIL8PfZBm6/LhrTxAIrL9SOkq57pXPsN4A9IDx8WrLFdyJuSYAmyZ9n0+6Escg7/e+7kprfvvQ2dv3H7j+65MHVuVMbQOSHXKoJmXi9u8peGou+11ayfXKR80s6uFkcbbJsilcw0ZK46Gu/L0gzObWLbacyDbyFegN3rHFnr+5kJ/MA50vAH58jLJDTzPavBekV8fs3mSTw1XFZ2IZs6bGHIe4sS6rizxTjVrHsuTDWaRqVbJM28Xl63gHaPItAWPjlJAqQL6ebPpt75zGUyUs/8kuQfRxbOaUKbRs+hiMB/+wCXFtBOGqY5f8PUQi6ukJkWU6YTyDsxbXcBsk3ZHUhDkgC5DC9EySto+TwTfYk3co6foc3Go8m/7DSMInkEbTTnSTC1G7JAa4URgRtxYeOYMq5KrRnRr6tEXgFSeSe8BLYuuwN5cWPRP0t0gLWheKaFURFZDaNM/kX+jciopGRRzKG7B/sC6p1tl3Da9u/TbOy89xHhq5ChzvlJ1M+wk4IbuteKm+Cd4Jy/MaZMkddL4nzyPbMwC7V2YU2K2UAvdRP9ZDTrOgCZz4bxnHN+Hp7Nu2FUidsKaGN4AW2k4RXk/7ECssQK+oFc6by+kOL3Hl9y/u5JNcxHp+as3xeZ/7cjbZPiOk6FtQVKyzo+oY3xSNc8tKA++flnAW00Ons0OotbyZ8Y6kCkEpmcvzuJfB2ZcH4B7b88jVRw26JB8Vq051g0jyCjmB2QKu1JtGoahCzxLmvCNeMowu9pY+KjRVeV/cruQBHMBO5JWfYeZP5ZNEUs4QzjSfJ/jxqxUsuqwnJZHPg2WvnPRrPxB5GaOMyqrSiV0rJI2I5DpuXTkJbh4CZdL44iIgmckOP6ZTEAOWO2hQorjueRc1y/hHL9nHJRaq48ZP3Q5qFZ1E1N6JPRfhSRmGcyPS8/SJlsRP5n9peW9zo/X6U44VGqAHG9YoMxefz0R6FCamjGVDRpUtYOBfZFwepecfpyL/KGNQzQj2gqrV2FGPnoR/4oFGNb3ekCGE2HCJD+yDu5hjyi/4Ti3pzk/P0zXt7p0eQzlSyKPniBCUfT/t6oRnH8hvw/xhnA4Bb3uyfzJvmfWZxJdNXYlmKFR6kCBBRa2o0OGnVcR7Uyt/VGcaFqtKcO1GgOrols3uM/re54D+Zm8j+v81re6+z8hw4TIC5boeX71SjE95XAd6iudP8x+vDi8n0bPY9RFPOjtLzhreEc8j+rMbSHJmIXihcelREg7Ya7EfVR2R0xKsXGeBGL8xzzkb+E0Vz2oZhB9Eut7niDLIks2kyAVIQReD90w/DzR4r5YX5Mc3yfDI8l8ZJz5TlepXtCtCrxa5ojPEyAZMTNYjgpqaDR41iZ4uzsP0Z5zzuRLqqRSuEeinlW3291x1PyJfJbm1VSgJyInIoGJ5TbFXmM79/k/qRlZzw1xf3ldsWoKGdQ3A90GsoB3imsCHwXeJtqhAIp6lnNQTnaq8S+yGetWcKj6QIkboZxJ0qMtCX1HrRBVkaJZUYBhxTWM5E213oXsCrykD0cL8bXKcis1zD89EKpkYtMuXoJ8oVqt9S/oIyYe6OUuYc4/4NicpW9il8deIdikt+9h5KsjSugrbwcjrIuLtnk6yyFVtwt513nSMPrNMdpJ4/kfYb2zwlgNI+1KMa50H+8jGaV7UBvFKr+MqLTGldhBQLK+lnUM3obPfuy6IXSXTdTbdWyFUgcs4nPtufnXpqTnSzLB7YIhTBp93wARvNxc9gUffwb+EwL7yMtK6JVxvVo/ybpPqoiQL5Asc/nQ8qxotsCBZ5theBoiQCJU2FNR4HUdkrRzn1Iv5gUN6tRzklZroYE3gQUffOdgvthdC6/QxFwm8FzTvv/ACY26RpxrIV+vzs6xxAa2xivggoLFGHiNRSluCgWoZTQZyNh2kw2ROrNL5M+jXhRlKbCet65cFx6TZB53CfoARtGu9Gb4hwMo46FwMNoc3pXYOmC72EFFAZjOAr1fjdemKE8R1VWIKB7a8az+RjlVyk6B0p/tM8xitapqyq1ArkIWUBcgvwqojgfean/Fm1aG0a70Q+pYVtlpVMD3gDeQhu649CAPwutpGej3+biaILW1+nj8r5jBbTCWIvkSV5WqrICAQn6V4D1m9T+IuC/KH/Mw2gPtZEUFQNRxI4d0Eb9HuTbIJ+Lvo+HAj/I0U5TVyBxAmQVtCk4EG1i/R59qNOQVBsCfA3d4Czn/7eb1VHDaDIroJwbGyUV7EFUSYCABuW7W3SthUgVPg6pxl3h3gsJhiXR4LwGEuLLFHz9byIHw0NQTLCslKbCAi23kzbbpmNZ/4zOYBDwOOWpG6p2VEmF5VJUJIEqH7f77nftnG2V7om+KlJnvYTnoLcIme7+Gt2gYXQKA2hOVNR2PKooQJZC6r+yP5tmHWORtZyfKTnaK12A+OlC+tYinHoMo6r0RWkKyh5Myj6qKEBAVk1pzJDb7XgfJckL8mCONislQAyjJ3ES0nuXPbCYAOnOrmijuezPqKhjMrBZxL3mCbZoAsQwSmQIMiYpe4AxAdKdfSguMGaZx0Rkhh3FsTnaNgFiGCXTD80Ci8gl0k5H1QUIyNR1EuV/VlmPp4A1E+5x6xztV0KArIKysN2BTHVnIsk/BrgN+AaNmbEFY9s04p35rK9eGhNDN0d6je6e7csApyIfgA9R/pCP0YzzFqTCGNxA30Aevz9DIQsmoGX2ROSV/FtkitgID/v6/7lA37/u9P1d5zofoFzwZ5HfMaroZ+6nNwpk+BMUtPMdZM3nfv5vIO/t05x+pMX/vTrG935/5AV8G8qzPcO5n3EokvQppPuhbYbMSMsedJp9vI9SwbpBFavO2sAjlP+5NXpcRbp4fYuj30aWa5QqQPqiwF8zSe7ox8h2OQ1lCZDLfO8fgAb2pPv6ecp+bQLclaK9Gkq1u3nKdv0C5CznvT1RZNG4a8wg/fPw06xnDrLoOx8J67Q/gHnAuaRLS+r/Xl3ovLcTEoBJ15kE7JfyPg5BkRfKHoCKPh4CjqR9BIef3sjhLutA28pjAo1nSXwh47VKEyBZzRmvItlKqywBcpvz3pdIr47YNcU19qDxyK4zSBe51S9ArkXCo5EfyfkpruHSzGcO8JUMbbtHmrD8/u/VKOQV3EhGu4WkXyH2QnlA7stxT1U4XkHxoIqMM1UmGwB/p/zPNeyYh1wisgzq12S8ZikCpIvuA8lrwLdQBra1kLnZXkg3PCtQ9scJ7ZclQJ5Cg4prvTEbRSY9CRgGfBblU/89sseeQvJsbEu6D1KPAyeg6JtroI3Yo5C6xl9uPlJ5xeEXIO/hmS+OR7GVdkBqto2AwwhXsRyacA1o/jMHrW7GO+XnOtc7AwnFjVDuhyFo0/DJkPtICjXi/159hFQx7v83IhXgJuiZbIey1AX15+NofAY+FPgTiglX9iCVdCxEas4foO9np7IdispdhRXJNOBSwk1003J6xmuXIkBOC3TiCuJ/VEOoV0ssQhs/UZQlQD5BOvAaCrm9aky9LmRvHseSdFdl/ID4EDFHU7/6eRdYNqa8X4C4x33EfzHOCZQfT3Kk5GY/c5ejkdprYEK53sDVgT79OaFOWN6IWchaJ4rB1AuaGukTmQVZDK0qL6OYYIZFHIvQKuNyNIlZIeO9tSurINXvq7T+s38BOBk5P+Zlz4x9aLkAGUC95+NDpFNPHEZ9x+Pit5QlQNzjX6TTqSdxUqDdv6Ss951AvfNiygYFyDSUBTKJ4Grn6JiyrXjmWRhIvZnmGwnlwwTI8BTXGR6oc0WWzgbojUwzT0HqB3fi0sxjARoo/4bUUgdgeXH8rIOexz9pbB8u7fEJWvWcQOPGNx3DydR/KLunrNeL+pncXKKjUZYpQGYDKzVwvTj8s5r5pBvYQTNV/yb4JKI/q6AAuSyiXJCdA/XuiinbimeeFb9abU5C2eD36kXS5b8YgFQ7br0ns3Y2geVRoqmj0Kz4CvRcnkGhgcYjFeUctHKYhwTox+hzfg14FO3ljURWbCeiVc9GWAbORlkV2B+pUX+NBv/RKEry+0ggzEHfjRnIyvFNNAbdj57fGWgvbEOKmZS2Pf6Z68c09qHcQrqBqEwBMrKBa8WxTqDdfzdY/5eB+ntFlAsKkGEp2+9FvRplBtGrilY886yMDLQfJ6CC36vvN3Cdsb56YzL00zB6HMEBpRfalHV5CUnftHwQ+H+tLJ1qMvcV1E5w8/vRBus/Evh/55T1XkhZbhESti79Cd/TqfozXxD4vxHhNrqBslN9ryvhfGUYVSc481+d+mxpO6EZWVaqqH8tKnNiMLHNKw3WD5ZPm4fi/Qau8Qb1K5s1Qq5b1jN3Bdf2yCdmNafuQLx8C0uQTy3zegNl/ffcSNpXw0jLUPQ9e77sjhRFUIAsV3D7VdTJTimoneBn9UmD9YPl03z2C5BVUVqmBf5fJqRMq5/5Usgk8Ws05mWehSlNbt8wGuEKFJHiq2V3pCiCAiRsgOk0giqRrATTiDaS/hK6C4I0ebIXNXiN4KZzmClvK5/5lmgDeLWQc26YlMlo4J/pHLuRPY1po8/EMJrFsijl7XNld6RIggJkZuD/m5GFTlam56gbRZI/Q6sI3luj/QoKoOBqIYy+aA8g7R5FsE/B5xv2XrOe+eoobtdA33tjkPXL7XhmrkGup3l5sA2jVexNB+ZRCt7Q5MD//dEmadYjbMDKS1U2OIOfVaOqoKDz4Mcp6zVy/8HVxdSQMq165j+lXnj8C9gUuBgvw1wYth9hFMkS6Lt2o/P/VijszUS0Yn0DuCCibhcK0vkw+i3NQvsZZxJuHbgzslIciyZCAMfR3X8keL1tnPdfTbiHsN9Mlvtzr/cTNL5chEyZ56LxYRTSHnQjuAJ5D6k9XD32phE3kJfgjacdJJakOB+OvAQ3ozdpsH6wfNrN/XWQ30AagjP3d0LKtOKZL4kCELrMQdFx06iY4rz0DSMrqwC7IPP7T5BqaVkUcTksjH1vlKXycDRJcq0VhwA/QuGCdqN+Bd4XuRrcjX5XO6Df+cOBtpvhd9To/YEiSdzr/H0WRckYgvxc9kIGL4lWoPdQLx03yH4PkQSDnaWdvW8fqJfFDyRPPBo/KwfavbvB+pcE6kcFVgz6gRyTsv3e1Kf9nE70ErrZz3wjsn9W7wbqxq3AWulfZLQn7gz9QxT37HjqJ7CDCPci/65T707qB+Dl8QJq/jHmuiOcMmmiHBSxAmnk/tzrufX8q40BeFHGrw/UCx1Qbgv8n0cfHkVQbZJ29p4mKGCrcHNvuOxK+OZwGH1RGBCXaXSflUSxf8pyu1I/e3+E6E34Zj/zYCyg4POPYmvy5zUxjDBWRMLgMuoH4klI5eRnSeRxPgeFBPJPMCaj8CigkDjBvc2yaOT+/JxBvYZjBgqLAyl91QZQH6F0PvINKJKvUz9TvCRFnRWpj9dU9goEuseCujZlve8F6sXlHAmuQOaTboUQXFXE5R9o9jMPeu2ncbrsRXhkYVuB9FwuoPv3Ic3hX937Z+9J0Z1d9nDKR03yupA6tkZ0dO0RtHYF0sj9uddbSLgAHOicT23BGgwSOI36GXMcm6JkPqGbLg7ro9mw2/48FCMoiuXRbD/4xShbgPSm+wB/PvHWFkdRH413IvExtMKi8b6ABGoU5wXKjyM5RlUzn3kX9cm7FiKnqigWR4EpwwYDEyA9l6IFSFqn11MauNaBEW2MoPUCJO39udcb1+j1on5gv0MbPm4E16VQhM/nkbrjJbQx0xf5L6yN1FCfwVPj3BHT4TfQ5s5nnf8XQ0HzfodSmb7rtL0G2rw5Ealj5iPTz2bsy2RhIcrg9izePs5ZKLPd5cBjaIm7DNqM+jL1X+YaSrIUDAcSxRRkmrsZ+nL9Fn1u49FnuBla3QXjav0fyRvWzXzmNbQ6+6bzfy+n7OlO29OQkFkLhV4/Fe8ZP0e8sGkXFqAJxyjSxzMrk8FExwT7Hl7Gx3YmzCoxDNdHazzJfhwTs3encNLen0uhVrOLocRKWSR+jeRMfmuiwbWRNr+K8m1UZQXiMoTkFLPBYx7p0lr6VyBPAF+gPnJs0tFIRsJmPvNByAosrN4MwjNE/gqZIfrfa9cViHt/tzSh7WawCpo0fEj3Z/PdkvpU9Aok7fdjhFP+xoRyadooYgWyPOlWIGnvL/OKJ07VMh/NZo8gOQ9DkIcINxn18y7Ss6eJITUVzd6vSFm+1byAMqCl/YI9iUzs0u6ZuAwCbkDGBB8mlJ2JvrRnJ5Tz08xnPgmtjF4MOdef+iCJc1AmxG+hFVAj4VuMYngfqSZXQhOL3crtTqm4Y86QFl3P3WuICgu0Vov6kUgaCXUDMrvdD6kXdkSzk+WQRJqGhMEraLb8H9KHw34FPZTDgINRAp4VkQ78I+BtNGO7Dm/ArKIAAa1ADkcz5sNRBrHV0ec0Ff0gHwZuxQuf3iiuVdUo4EG0n3Io2lNaAam4xqKEOSOJ1mkm0axn/jr6fI4EPu+8HoR+MJPQ8/438FekLsA59wQSuEY5uKvEnspDSH27IfBpGo+8DZ4KeZkUZV012GpoxR387NNaYhpGnQrLYju1L+2mwgri9xXoaSos8FI+v42iR/vpQiauh8fUd6Ncf0I60/S3nPK/pl5TtDOawFVehWVUDwvrYRjl8EvgD8h45FnnuNP5+zHwAPLYjuIRZEk6EHgZOR+62SiPDynvJkM7Ba3u70Kq8geQdmBC5jspEBMghtEasqgsjepQQ/uD+yHLwVXQvtDKaLVwIfDjhPqfRUYqU9CKZHs0BoftZ16PBNLDSHXs+mWNQMZEVVXlGxXDr8IKhmc3qsMX0CxxEnpObyELwDWd89NJp8JaEVnOPYXUHXPRftDNyPw3zSp0M+AcNMv9EFn8zUT7Y7egPahGV7OdosIyjB6FCZBq0wf5y0QNXlNRnvgxJAuQQ6nXb4cdd1Af1TjIZSF1wo47kbFKWkyAGN0wFZZh5ONCPI/9d5HT5m5IXfEjPKGRZH2zPzIDXwrpt89EEYz3Ak7Ai7u2D3AT0bnhH3H+vgb8Aq02dkEe0t/Hc1rdG6lDDMPoYGwFUl3WxbOuGkN4mOyNqV9V3BJSZgBeqJcniE5ONtLXztERZRZDEQWiWNvXn0ay49kKxOiGrUAMIzvH4K0Efki4B/sraC8kjq/gCZ+vEu04+e1AnTDmUx8lOsgYtDcCCrNvGJkxAWIY2XEDgC4ifm8jGC4/iBuA7wPiVwUf4amg0kZaDcN1MO1LY/sghlFHI440hmHUs7HzdxzxOe2Tsk1u7fx1k5SloZ9zhK1WeqG4ZPsgp7dVkSmoW8cfIsN8i4zMmACpPkXnYjGKY6DzNylBVlxU1N5kT9vbl+4C5FMoZlwwSds8px8foH4PzHhNw/gfJkAMIztpZ+8LkZorTGXc5WvnaRrLBjk98P8WKKf1Emgv5DLktfw88pZ2uQI4roHrGEYoJkAMIztTURDLpBXEAKL3Gxc47SyDkn7FbYAncQGeeuowFHQzjMVyXMMw/odtohtGdty9jbWIz4W9fkI7zzh/NyR9Frkw3JzVbxAtPMDzjjeMXJgAMYzsPOT87UV8IL19EtpxrbR6oXhLWXH9R+L2XFZG+ySGYRhGiWyE9jZqwJt4aY39rIbiUSU5Erpl5hIvjEB5VMKu9bbTxvSI84sD/6LeyS4qaVEQcyQ0umErEMPIzqsouirIK/0ptAm+CwpB8n3nvV7Ep8mdgbJAzkeWVaNQYMZTUSiSo1E+ij+hII1PIdPcIG5GzAHA7ShcyWBkbnysU28/tKneCH1QiBWXoCmwYRiGkYHF0YAfNfv9GGWxu53kYIo7o8yWaWbVYV7kS1Of2z14LEIpjj/ley9MEGyNcla8h4RbVHtzkXPjm8B5MfdVFLYCMYycrI73w7i75L4Yogv4EnAP8glxw7n/GqmwAH5OsgABDegnIoHzHhqk3ZDudyMBEBeCpB9wFvJon4WyWL6L8kvs6JRZ3GkzSoDsSuOD9MiE+yoCEyCGkRMTIEZPxQRIxWjXPZCDUIC61ZIKGoZhGM2hXQXICLRZuULJ/TAMw+ixtKMA6Yc2JQ3DMIwSaUcBsjMWgtowDKN02lGA7Fd2BwzDMIz2ECCHAZcA9wOfoJzTLs8QbXkR5+g01ilzlu+97YC/IJv2Wch+/wXgdyjKaRRLIxPOa5Dt/DTkEPYJMqW8nMZUboOB3wCv+/oxGu379EXml41wMDLhHItMOqcCL6LPNClGk2EYRlvzItlM99IIENeL+Dy8kBRhx8ER7QynPt913PGrFPf6eSQ0otp4AQXCc/saZ8a7IvBAQp/mU58m1TCqjJnxVox2COd+NPWRTs8B9nBefwWtGMJIM1NfFTgdOWfNR7kUXkDJd9ZAyZxWJXqgfhkvxMMraJX0ChICawIHoLhFoBXEY2g1EMangb/iPZPRwM3IMW0VYBiKR/QvvJAXUQwEHsZbYbzktDUWCdbtUOiMxYGfOmUuimnPMAyjI7geb2axRcY2xjr1J6LB+EGiQ1yvl9DWCLpnf3PpQv4qbn/vi2nneV+5CwlPVnQO9TOrKMF2na/MzyLa2hQJpxrKSRHn3WwYVcBWIEZuihQgNbTXMKCIjkXQH+091IjOm/0ZX39eJnpvqgsFxIsTIBviqbj+S3zWvJN9bf0x7iZ6OHeTbeDaoYzOZiDLvc0ooZ+dKECy3pP/+GHLe+3QDpvozeZCmvtjmIkS/IDUXWHZ4PyWZVchARBGDbg24XpH4gmNPzp1orjF97rKPzLD6ER+jCI25+F04NwC+pIJEyDwnxZcw5+PunfI+S19rx9LaOuZhPM7+l4/nlD2PaS+Aqnw+sWUNQyjOC4Evpejfg1pEH5RTHey0Q6b6M1kETChgHbWx9swXxelJV0a5bhegmTHxxV9r8cllH0/4bx/L+elhLJBlkMGAIZhNI+LgDNy1F8IfJXWRECOpacLkPlEq4vSsBoyBT4wpswC5xpxqz2/lVnSAD4z4fzSCefj6OnfB8NoNj9HycGysgA4CrihmO7kwwaM7KyATG1Xd/5/E7jSeW8MsnCagR74aGD7mLb8QmPJhOvGme9C/X7O8WgDPy0TGyhrGEZj/BL4Vo76c4HDgVuL6U5+TIBk50w84TEKPdh5EWWTPmf/wL0qSkYURVIE4gl4pscPICszwzDK5VfI5D8rs4BDaM2ebWracRPdb1UUZ6LabHb3vT6baOHRBayV0NazvtfbJZQdmnD+Qd/rXRPKGobRfC4hn/CYjiw1KyU8oD0FiH8PoMyEUn7fkSkx5fYDBiW0dYfv9THEP5cvJLR1Hd6+zqkkq8QMw2gev6Y+fl+jfALsRf3EsDK0owB51ff62NJ6AW/7Xn82osxQ4M8p2rof776GoNhcYXwd2C2hrVeQLwnIqfBWFAolihWAk4j2xDcMIxu/BU7JUX8i0nQkmfaXRjvugdyIHHAWQzrBB9EexGRkzbQCsCzwzSb341pgT+f1xcAGTl+moZXR3mi1MBeFMIkb+GvAiSgWVy/kXLQ7il81CVgJrWR2Qd7lQ4n32TgZhSrZ1unjWOAeFJhyplN3dSSsNkNqtkeBd9PcuGEYsXQBl6IJX1beRzH/XimkR0YdJyJb6CjX/ikJ9cc65ebk6EMvFPwwLsTAR8ix70jfe3FRgr/k9CmqvSeROuxp4mNhgYTElcRHGXaPBcDG6W+9x2GhTCyUSVq6gD9k7Kd7vENyDD4jJzugVcBYNOjOQVL7UZK9M8eSX4C4HIk2tyYhv5KP0QD/I7y9j8GkEyAgR8RLkVnwbKQDHY2Wwm4YlGtJFiAuQ5D54NNolbYAL7zKLWhzr8y9pHbABIgJkDR0AZdl7KN7vIGpkw2jozABYgIkiS6UPC6P8HiJ+P3KytGOeyCGYRhVogu4gnxGPc8ia6tJRXSoVbSjFZZhGEZV6AX8iXzC4zFkZNNWwgNMgBiGYWSlFzLT/0qONh5EK48pRXSo1ZgAMQzDaJxewF+Q429W/oP2Z6YX0qMSMAFiGIbRGL2RifyXc7RxK3AQjQU7rRwmQAzD6HTypGwI4gqPo3K0cQPwOeRk3NaYADEMo9MpyuS4N3A1cvjNykjgi3iZQNsaEyCGYXQ60wpoozdy4D0yRxu/Q9ZaRa6ISsUEiGEYnU5eAdIHRblOioQdx89RjLpazr5UChMghmF0OlNz1O2DYt4dnqON88iXA72ymCe6YRidTI3sZrJ9gOvRhndWvgNclKN+pTEBYhhGJzOTbHsOiyFrqUMyXreGEkn9NmP9tsAEiGEYnUyW/Y/FgL8BwzJecxHwNdIlk2trbA/E6EmshmaEbRXx1MhFo/sffYG/k114LEA+Ih0vPMAEiNGz2B9ZwixfdkeMltHICsQVHgdlvNY84DC06d4jMBWW0ZPYq+wOGC0nrQDpi1JI75/xOrOBQ4E7MtZvS0yAGD2FvsTnpTc6kzQqrF7IzyOr8JgBHAjcn7F+22IqLCMtg5BlyZPO/3ujTH2fIEuXp4CTkMduFNsBF6P0utNQCuBJwEPAN/BS9oYx2rn+IPS9/YbTl2nITPNF4JxAnfWRLvppp4yrunqB7tngLoy5ttG+pFmBXEJ2U92p6Ldwf8b6bY2tQIxG2Qg4Afg9Xh76QcBWzrEH0gMHTSe3R0LAZSbwHrAysJNz7AsckHD9tVACH1dPPRtYEtgUeCZQdhCwDhpEHneuARI8MwNl3064rtGeJAmQ76LJSBYmIeER/N4ZhhHAXYHUkKXJCKQWAq06jkMrihpaiYRxpVNvDd97fYFv+9reJaKuuwJ5CvgIOBpY2jk3AKkftovp/wDfNTaLKReG5URv35zo58S0dxSa6GS5//fRpMUwjBT4BchVEWV+6Zx/K0P7jzt1vxtx3hUg84AhGdo3ARJNJwuQUyPa2hN9l7Lc+7tIPdrjsT0QIwu3RLx/rfN3HWBwg22+4fxdJqHcbWgPwzDSEKbC2gJZXMXtuUXxNvAZvO9rj6ZIAbI6noT+jfNeb+BbwGtoxvI8ssP3b7QuAZwFvI702W+h2DEDUl63N7Az8BPgTuAdtGE6H/gYPeh/AKeRzoFsLWCh717+k7IfQX5D/awlq4VHFYnaL3jF93q9kPP9karrr8CzwHi0CTkX5UgA6Eq49tOpe2kY3QXIWsC/gKUytvdjNMYYBeMXIHc77/2O8CWgGx+mD/DviDJPos3RKFYFzgc+jKgfdswDziXeUgjgn746i4C1E8oH6YP09G4bE1Jcs+r4VVgbx5RzdcoHB97fEfjAObcQbTz+HbgcWcG85pyLsoZyVVgjMvXeVFhxdLIKax9f/eXQJCfL/brHdGDz5t1iz8UvQN5D1jhxD+LTwJkJZaL0lwBfSagbdyQFODsgUP5HaT6AmPo/bbB+FfELkG0iyvgH6T187/fDE/T3Eb4SvAkTIGXRyQLkU07dJYBHMtQPO94BVmrmjfZE/AKkhiT9i8j7d220Oeo//09gClIzHe2U2R+Y7CvzbMz1+iIVSA2pQP6DYu7viUxNV0ebrcei1UzwS7B9TNu90JfELTuBxkyebwhcK27G3i74BcgXI8ps6yuzlu/9fX3vrxFSD7wftwmQ1tPJAmRT9Hv+R4a6ccd/kVAyCiIoQOZQP4iAVBbBB7FPoMypvnOLiN9UPRr4JjAwoW9uLmP/dZOCnZ0VKH9wQnmXpdFejv+L1gn4Bcg/Ispc7Jx/M/D+5533FxK+cbk+nglwswRIH7z+N+qRbgKkfQXI6sClGeqlOa5r7u32LIIC5NaQMp8PlHk5pMzmgTJbFdS/gehL77abZEWxMvVmfrenvM5x1Pf/+Ax9rSJ+AVIDzsbbo+qFVnpRfiAb+up9M3BuDyRwXMOFZgkQ8PTf/8bzIXHp2734/zAB0r4CJGoftqjj7KbecQ8iKEB+EFJmg0CZ34eUWTpQpkjrpf/42p2TovyNvvILiVa/+LnPV2cWyWap7YJfgPwA7zN8C4Uzcc/9nXDrvmt8ZcYggeBuqj+K1I/NFiBHUf/83wLGOa9Pj6lnAqR9BUizj0Uo8kKPpJl+IGNC3vso8P9rIWWmoQfjEmeJ1SgTfK8XT9H2H3yv3Vl2HGtS70l9M/nyMVeVK5FgfxQJlsWRee3JwBcIzwA3HK1MnkbWMJuhjfUzkUrprmZ3GgmxYcADaN9sTbTB/zz1JsiGkZYu9HvYtuyOtDvBFch+IWWWCJQ5IqKtOb4yXyqwj1cErp/ka9KFZ15aQx6ocUL3e4H294gp2274VyAbltyXVtPJKxD/3pCtQLIfE9AY2KNoZjDFNInsZ6Uok+RYBhrUd0CWVZujzHPLo32PJZ1jCRq3mqgBlwE/d/5fA1kU/Sui/FG+1+8A9zZ4vXYhzTMx2oO4vZ+exCtIW5BV6K+C9n0/Q/dAnUYKgiuQMDPZ4Apk34i2/CuQoyLKgLxJz0XSP8usIY23+3LUW1X9I6Lc1oG2z03RdjvhX4FsVHJfWk0nr0AG0rNXIHNRwMW+aNL5Rs72bqYHTbCauQJZ2MS2AbZEcZFWCzk3A+3BTEa+JjOdYzcaD4L2MdpMP9r5/wA023g/UO5o3+sa0osaRtXJEg+qU3gYWUm6+1+T0d7eaGDZjG0eghyPz8zdux5GcAUS5q1c1Apkdeotf2ooPtMIJCCiZgDXB+qkjbf16UC94JejN55FUQ1ZYnUatgLpzBXIevS8FcgU4ESix4ndyB6p1z2+XNA9V5p2jcb7U+qdB/+FPE4vxluChpF1afkostRx+Wqgrb2pD23wl4zXMYxWs3xykY7iZhQZ4g9EjxP3AV/PeZ3LUfy3jqYdBciSaJnoMgdJ+9kp6mZdlgL80fd6berNdf2WYjNQXKdOYxISml3AqyX3xSiO5cruQIsYj0y4P0d39XMYf8IznslCX7RfOjhHG5WnHQXIWtT7bzyCdJdpyKN6uZr6Zftw5++S6Ivp8jfMCsNoH1YouwMt4GpgE2BUg/W+k6GOnxVQzL+soeMrTzsKkODDSCs8tiadJ3kU01EeC5dhyIFuH5TnwsXUV0Y70WiqgnbkOtK5FQRZhLQLz+S49qZo77Xd0zmE0o4CJCgw0giFXhQTUt0femUZtNl2oO+9N5Blh5Gd4Ug3/WLJ/egprFN2ByrOTPQbn5BUMIbPkk8dVlnaUYCMQfp4l+2BoTHlF0f6zCK8wp9Bubtddkfh6l1GFnANo3NoB3+AnrACyct7SIikcXyOYgSdE1j1f7SjAKnh5d4G3cMdaKnpRljtQptXJyDrqeHO+88VcH1/fKxD8FZAi4CrCmjfqB5ZfZrawct7SNkdaBOeRmNMlOVWGi5Fk86OoR0FCMge/F3f/yujQHlT0Ub3fLRS+QOKAAwy8U0KhpiG65EdOdTn/b4LWXoYncfcjPWqnnBoPZJz6Rget6DEeFnpg6JVN+rMXFnaVYBMQqqjMD15f+o3rOYA33KO58m3DAWZC4etNGzzvHNJE/o/jKqbyG5ddgfakItITkYXx7LIMiuPS0FlaFcBAvA6SjZ1DApp8h6aKc5EgQzvA76NpP3FTp0FwBMFXPsPgf8/QbMTozPJKkBWLrQXxdNoZkZDnAjcn6P+Big8UjNDSRkVZn3qwxZcWm53YukCjkRZ+D5A6r2PgZeQWfIRKCdGFEOQccA7SEB/gvJpHEvyBCRL3eHEW2Edh/Yk5qHcI63gYrKFs7i4Rf3LyjtkD9XRTqFMokIm5WFZ6lM9ZDmCE1Gjh/Bj6r8IYXG/qsJIvH5ORTHDpvrem0d9GBY/x6NVWw0JnnfQCs+teyeyciuy7nCiBcjJyFhhJvK/aRXfJtsA0YokWVnZjHyDX08XIKCJ5OSMfXKPbzapb0ZF6YU2y90vwAvldieWLVAf56A9I79Z6YrAV5C3bRi7o5n+HCQM/FFb98ILoX9JwXWHE/65nu68/zHwqYg+Nwt/KtxGjolU15T3IkyAFMGu5Au8uIDw5HtGhzKM+i/ASaX2Jp59UR/HZqj7uFP3tIjzRzrn59I973ueusOdc35/m7Oc9yagmXOr2ZnsA0QVzWQXoz56tAmQfHwlY7/cYyryWDc6nN7As3gPfjLpQ8KXwQroh15DzpRrpay3Bt49huVbwXnfLbN3QXXBEyB3O/+7g8ablOf0thzZB4eoFV6ZZF1RmQCJ5sKMfXOPt+kZccl6NL+g+oNDkMNRHKAaUivdgzai4wK8HUBjX/6jCqoLngC5CW/vYQ754pgVgV9t2chRhPNqkfRBwtgESLF0oVDxeT7Th2gP59P/YWZk4eyNdO0T0UC7IXAK9SHcX6L6Vjag6MAPoM26r6D9id2BXyHrsQvoHj14GefvIhTfKwl//Tx1/WyPF7Z/cZR29LgU7TWLZ4leUcWxObAT1YmRdhKwbtmd6EDcydCDZPev2Qm4DC9yhtGmuGqfqGMa1dRtJ9EHbdjdhFYjNbTXEExrepBzbgGN+wrlqQveCmQh8DsUiM7NSV9mmtDTyD6zvKOE/oaxAfWWcLYCKZ5Vyb5adY883u5GBYgTIO+jFLftztYoJIs7c/KzNt79btVgu3nqQrgZ7+FoRbOI1vl+BNmcfIPCsJb3uJ4BKJ5TEcLDBEg8W5I8CY07FlH+98XIwSgUS2sGmklPRiqI79DdaqiduR19YX8Qcu5J59wNGdrNU3c43QUIwBnO+7MpT4C/R/ZB4X00Oy2DvsgnpSjhYQIkmYPxVvlZP98tWt1pw/BzPDKBHUq9OmkxlNrTnSUd2L0qOyMHwBoKVOk3M1we2BY4j3Dhk6fucMIFCEilVUN7U2XksfgZ+Qbdx2l9drrlgHtz9tsESDZc36WsxzhglZb32jAc/D+42chU8B0UUNJ9/3qind0Op34pPg/5bvi/5NcUXHc40QKkN4p7VkN52VsdkG4T8g+8o2mdueYOyJChaOFhAiQ9l8f0K83xOPUpvA2jZawL/BJ9CSejVcE85JB3O4qDleQpvQbyWn4OmQPPRuq9e9HG8poF1x1OtAABRVt2VWT30Xqzx4fIP/i+R30isqJZCVnY5VGhmAAphsWQ6Xyez/oGqhvRwDCMBtiT4gbhW4DtCuzblijtsmu11szDBEh6BqIVc57P+9xWd9owjObwAMUOxk8B30fCJCo4ZRirA59HDq5ZnQOvJZuu3gRIY6yH8hjl+Z4c0fJeJ2DLIsNonKEor0zQf6YI5gNvoYybE9F+1QKU3bAfStu8JgpLkzeMzpto1bIy6Zw+/cws4PqNcgEStI2yH9XwxdkZWcNlVbvOQcEbHyuqQ4ZhlMMPab6aqJnHPGQNB5pITm2wvq1AsnEM+Z7b+5Qf1scwjJwsRvGqrFYeXwvcz4MN1jcBkp1gPqFGj2epSBDXdk5paxhlMh/F6nq97I5k4AxkXurn6TI60kP5PgonlJWhaO/Kxm/DaHPWQf41Za8o0h5R1jzHNNiOrUDysSRe3pysx0Ut77VhGIWzMvV5Yqp4zEHRmKNoNNaXCZD8rIyMJfI81+Gt7rRhGMWzFHAl5QuKsGMc3oZ5FH2QkDEB0lqG4uXryXLMBT7T8l5XgB3wPoQFJfelp/EZFNJkCtVOyduOHEb+dLFFHQuA35A+5MsTDbRtAqQ4DiRf1ICyYsOVigmQ8vBnTvuo5L50Iv1RoMhplCc87qHxnDWXNdC+CZBi+Rb5nvfLlBAp3HbxeyY13+v5BbU5CNiI1kebrSIzUbThNYH/IzquV9HMQtZVWwB7AC80WP+ZojtkpOZXwB9z1N8YxczqXUx3qo+tQMpjR7R5Nwk4sqA2b0LPsnLhFirC5sD3UDDGeRS30ngfuAolBRvYqpsxDCg3lMkOwH+d1wux/OztTG8kjAYigXR9qb2pPn2BzVAYkY2RZ/FqKPfDUihsyRJIQzATqYtmoD2rN4HXkP/JC8BLre26YVQDW4F0DtvjPUtbgRhGd1YDfkuHJYiqyh5ILbmIUWGamdvCMDqB/YGTUUbOjqEqAmRR2R0wMtOH9rByMYwysUlWwfhVWNN87w9DZqbvIMemicAjKH5PIwHEjvK17x/gVnDaGo02IOcC451rnE99/u44upy+XoVCYU9DVjBjgRvRXkAaAX2Jr59TUJjuJM7w1ZkDbBVT1v85hx3/THE9P5sik8ORKH5SI85nNaTbN4yeRF+8XCCbldyXjsE/sH2AbOdHET/4jAc+nbJ9vwA5znnvQOCThGscn6LtjfDSqsYdzwMbJLTVl3oHroeIN8Xbivrc4icntF+0ALk4ob2eKkCGo2cXFxb9/oi6B6Jc7x8iC60P0CRql4jyTzvtnZXQpx855aLyRwxBE4F30HfqExRh+FjiJz+jnXYHOeW+gX4P05BX9YvAOYE6A5w6rknzLiit8kR0z+PQZCzs9zLW6dfSaIyYiULHuNkcz0Epmz9GybWi+t7o/ebp8/rAn9Gz8v9ew44LI/prxOAf2MZS79z2MvpB3Ub3QHXTkZ17En4B8gPgs2iz3n3vQ2TF8m7g/dUT2t0WfVH9fXoZuBV9uV8JnJtM8qpmHbT6cOv8MKJcf2SB45a7MaFdUNC27dD9Hw2MoD5Hc6MC5LPIoct/+D+Pm0PO+49OtLb7E95q8HYUKfUNvM/kGSR4DwvU640GILfcNJRMaobvvZ+GXO9k59ybRFtS9sKLsxQM3Q6aKLnf+/loUJ3pu+6dRGdHdAXI1tRP+mb5Xl8dqOMOxnNR4MZFyPryHfQb8X8GmwTqjkUz+KvwLNJqaAD/Bt7v2W3j2ILuN0+fP4UmDPejiYVb9gnf++6RZtJqBAibGT+N7OWDBFcOz5DsMOMXIHc69RciS4j1A2UXd67xo4Q2l0VfHrfdxwj39t2KekHyCskz78/5yi8gfKX1Z1+ZN9GMLAtn+dppVICE4U+n2tOssPZA9z2b+u/CYkjA15BQCeM85/xU9Pzd73QfpAJ1YyQFV5kD8QbrqFXK3s75GXR37twd/RbmoMHLn1lxL2CCU/eSiLZdAfIUimRwNN53cQDaMA7mencH4xoaiK8BVvKd3xEvBEww1PlYvBXc4mgj+n28wd1VUX+X8O901vvN0+eodkyFVRBBATIRWC6m/F6B8sMS2vcLEPcLEJwBNsrPfO29QvyezOrUh7I4MUX7v/WVH0N9aILDfOeS9j2SMAFSHL9B931tyLkt8SYEwZXX8nhCIOozO8Y5/zHdhcDVzrmREXX/6pz/U8g5N4z4aRF1j8QbnJcJOe8KkHmkD5fiH0SfIFxl5K4mpgTeH+u8f4jvPTfsyv2+9zZ23ns1UD/r/ebpsx8TIE0gKECSZv9QnwEuKSFLUIAEE+g0Sj/q1UyfS1HnUl/5J1OUXxxPv10DrnPeX5P6FVjSvkcSJkCKw1W9XhBybiDe5xJUjX4JTzhEraYXw5uEHBI4twvRK4yBaEVUQ6oUP2v4+rRaxHVX85XZO+S8K0AaSYrkH0SjJlOf8pXxr9jH0n3w/aHz3m98763ovPee770895unz346VoBUxYwXlGw+iX/4Xgd/GEn8rsHyQT6NNzuZTbqB9wHf6y1JVjnNBQ7Hs0o7EuVwuBYvTMXfkWAyqsFE5+9KIedcpzFXTeXH3Rd7GalXwpiPVrrQXbX7APJG74++M36ORIPZy3jRHlyG+l6Pp36S5R7jfWVWjOgbZM9iGBWja7rvddhemf8znOv8neJ7z3UH8Avkou43a587mirdcHDZGYb/Ia6CVF4fp6g3E3guS6d8bO97/SreFziOCb7XvZCJblKAuzeRntYNB/InvI3St/AsyoxqcDt6XoehPY1xvnMjnL8PUD/QgLdqCL4fxD0/MOTcn5EFz1eoV1W5iaOuCKnjToIWoY3+JGZmPBfHtOQioYQF/owSvi5F3W/WPnc0VRIgk1OU+TDwf1oB8hH5nRX9IQhc3XajxO3x+LkB2BUtm13hEVydGNXgNmSJdDAy97wVzZS3B7ZBqsdTQuq5s+mk6MXu+eAKBrT/cQHazN0ArUg2QZaC8+huCQWeQKo5Zctw4s3y28lKUffbyj63DVVRYdVIF1Z8duD//inbn9dYd0IJ20xslMWSi/yPoH75deRXYlSLGlp9PIhUlJ9HK5IV0L7bloSHc3ef5aZET+QWQxvDEL5y/RBPlfpl5+8Xnb+3INPXIG47vUlnDt/u9LT7bSlVWYF0IYe6pIG+X+D/Via18V/L9VxvlA9Sllse+EvgvSHI0OA7Ga5rNJefAzsjc9ZrUta5E60mB6KV5XUhZb6IViDTgbsj2rkCWSQeiYwjDvO9H8YYZH67NfoufSFlf9uVKtzvHN/rFUq4fkcStMKKspDw49q2u0dcqk6/FVaa/ZUkzvW1F/VjLoIupFd3r+X3ZF0E7FfANcwKq1hmIl38jjS2yjwVb4P983ibv72RUHH9QOImDb3RvksNz7JrDPGpGnZGK/4aEnh+R9flkQrsPOSAG4ZrhTUi5hpB0lgibeYr4zeRH+u8t7LvPdfn4xzfe4Oc94ITtaz3m6fPQVy/sH/T3Zimb0w9I4KgAAkzFwxyuq/8+ISyRQuQz/ram0jzcqn441xNRuafp1J/7VVzXsMESLH8hXDrnpnIEuqXRFv3XOwr73qi+/2Hfk/yd+18p6zr5Hp2ij4fTr3H+zy6h9yIWk21mwCBbPdbpADxj0dz0HMe57w+PaZepanKHgikm1kP873OokLKwwN4FhqDkEApmk8BP/b9fxwSlL9CKg/32n+lWqkr/arHrN7x7crG6FksRCvEqc4xDc0sN0bBJ58kfMU8AjnJjkJ7fGsgB8NR6DfxdZI3cN1QKms6fQiqP8P4m9O3n6H9mLlO3bHAfWhQOzNFO+1C2fd7DRq/HnCuvSZSyT+PZ6ptNEBwBTKd+DhU+wbK75/QftErEFBcIrfNMaRPDtNFsmpjOerDpAT9VlaiPt7P+SmvHUbRK5D7fe1dVkB77cJmaFb7CZpQBJ9xF9q7cp/r/7W0d4bRwYTFwnqVen8LlwOo98R+nOTVUzMEyEBkDeW2+wEKVDcwpOxSyFv4ArRc3SGh7Vt97b6IgiAG2RfNmmpoxrtHg/13KVqAuFFfa0jXfGABbbYDV6B7ToqK64ao+UXTe2QYLaQqVlj3ogFxL6RffQNFnV2ENrzW9ZWdiqJtlmG/PgUNjnchVcNKaMb9RxT5dAqahS5LY6krT8UbdOegfYSgyTLAHUhn/i0kQK9FnrZB/xiXlYDByATZPQai4HIuG6BNWr/qZSraf0m7tP6j06cl0XfqVqT7f9M5vxT6PAagz61TcFfMSb5IbvDO95vYF8PoUfhXIN9Gg4t/Fh52vEv3KJ9RNGMF4jIIhRRxVwNJxySUQySM7dAeglv2pIRr96U+XtZdRK/GLkzZv7AjyUghyMHUb1KGHVMabLPqXITu6xW6R3gGWRa6wRZnI2FuGEYB+AWIP3T5QShA3Ti02TQJbZifTnrHQWiuAHHZDG16P4qX3XAOUm09ggaPg4jOqzAQ7aW4/bwl5XU3pD6XQZQKpZUCBDRA/gwJuCkoCu0UpML7F9Fmoe3KIOrzfryOnvt/qd/Pmkn+SNCGYRhGh7E0st75L9qnW4AmEROQdc9ZNKbONAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMIzy+X9X9rGERK0pTAAAAABJRU5ErkJggg==\n",
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\n",
       "text/plain": [
-       "<PIL.Image.Image image mode=RGBA size=400x300 at 0x7FC3EEE9A7B8>"
+       "<PIL.Image.Image image mode=RGBA size=400x300 at 0x7F41B7E9E898>"
       ]
      },
      "execution_count": 62,
@@ -2746,9 +2768,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<PIL.Image.Image image mode=RGBA size=400x300 at 0x7FC3EEEDD080>"
+       "<PIL.Image.Image image mode=RGBA size=400x300 at 0x7F41B7EEA1D0>"
       ]
      },
      "execution_count": 63,
@@ -2813,9 +2835,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<PIL.Image.Image image mode=RGBA size=400x300 at 0x7FC3EEC08AC8>"
+       "<PIL.Image.Image image mode=RGBA size=400x300 at 0x7F41B7C0CBA8>"
       ]
      },
      "execution_count": 65,
diff --git a/doc/source/version_history.rst b/doc/source/version_history.rst
index 448912c..007df2e 100644
--- a/doc/source/version_history.rst
+++ b/doc/source/version_history.rst
@@ -3,8 +3,8 @@
 Version history
 ===============
 
-0.9.0 - upcoming
-----------------
+0.9.0 - 2019-12-20
+------------------
 
 * added usage and API documentation
 * added support for Arun 2010 metric in `tm_gensim` (thx to @mcooper)
diff --git a/setup.py b/setup.py
index 5a749d1..2d9ddc8 100644
--- a/setup.py
+++ b/setup.py
@@ -8,7 +8,7 @@
 from setuptools import setup, find_packages
 
 __title__ = 'tmtoolkit'
-__version__ = '0.9.0-rc3'
+__version__ = '0.9.0'
 __author__ = 'Markus Konrad'
 __license__ = 'Apache License 2.0'
 
diff --git a/tmtoolkit/__init__.py b/tmtoolkit/__init__.py
index 08d7567..0c216e3 100644
--- a/tmtoolkit/__init__.py
+++ b/tmtoolkit/__init__.py
@@ -8,6 +8,6 @@
 
 
 __title__ = 'tmtoolkit'
-__version__ = '0.9.0-rc3'
+__version__ = '0.9.0'
 __author__ = 'Markus Konrad'
 __license__ = 'Apache License 2.0'